6. Case_Study_Paulita78_Watsica258.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[]},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"markdown","source":["#Synthea Analysis"],"metadata":{"id":"knphiOWgjdVU"}},{"cell_type":"code","source":["from google.colab import drive\n","drive.mount('/content/drive/', force_remount=True)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"OEAMU3pCkSPi","executionInfo":{"status":"ok","timestamp":1722377785442,"user_tz":420,"elapsed":2463,"user":{"displayName":"Nainika Reddy","userId":"15989986900907940721"}},"outputId":"5dfd266d-cc83-447b-97e1-4dff3fbf88e7"},"execution_count":44,"outputs":[{"output_type":"stream","name":"stdout","text":["Mounted at /content/drive/\n"]}]},{"cell_type":"code","source":["!ls /content/drive/MyDrive/synthea_dataset"],"metadata":{"id":"WhBsfIczlS1-","executionInfo":{"status":"ok","timestamp":1722377785443,"user_tz":420,"elapsed":13,"user":{"displayName":"Nainika Reddy","userId":"15989986900907940721"}},"colab":{"base_uri":"https://localhost:8080/"},"outputId":"224fb449-ea5c-4191-fb41-ab03e289c853"},"execution_count":45,"outputs":[{"output_type":"stream","name":"stdout","text":["'Adrian111_Bartell116_fd25b51b-dc2a-4edb-b7c9-2c5d178a0ee7 (1).json'\n"," Adrian111_Bartell116_fd25b51b-dc2a-4edb-b7c9-2c5d178a0ee7.json\n"," Adrianna470_Boyer713_6fcf56ed-8ad8-4395-a966-9ebee3822656.json\n"," Adrienne302_Zulauf375_1c83fb03-d139-4626-bb39-4a062c22b533.json\n"," Alaine226_Kassulke119_5efa5654-8190-4f4d-9ba3-3b79448440b5.json\n"," Ali918_Larson43_896d3035-d036-4c8a-9901-367dc8814495.json\n"," Allegra202_Heller342_cc4c634f-c2ff-4963-b75a-fa2e33dc208f.json\n"," Allena79_Pacocha935_d11e7fb0-5853-4762-b8fa-6cd9008a790b.json\n"," 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Sean831_Wunsch504_ee6e5262-c050-4397-ba45-e706155e4d76.json\n"," Sebastian508_Reichert620_d05c5dc9-d715-4d1c-ac78-0c474ab444fb.json\n"," Shalonda324_Krajcik437_20582f40-de29-4452-bf64-157e6d17c613.json\n"," Sharan181_Bauch723_3f583fdd-bdd8-4a38-9190-be132e5adc1b.json\n"," Shelly431_Eichmann909_eb5f8ed5-5eca-4ef3-88e0-d74f6c4270c7.json\n"," Sherell789_Heathcote539_e4effebe-a8b3-4fad-b241-e7f945d1bdc7.json\n"," Sherlene302_Balistreri607_2af970df-cd8f-45ad-9d0d-f625e20da333.json\n"," Shin962_Bernhard322_1a3a1478-08a3-43cd-aaed-558b393e0742.json\n"," Shirely692_Leuschke194_f69ecce5-eb1d-43de-a048-8cb4f33b4d4c.json\n"," Shonda871_Connelly992_6aa9f69c-2910-411d-aa2e-b5eaa7c3b1e7.json\n"," Shondra529_Moore224_3be82b66-8bfa-4a0d-9133-2b366e4cb88b.json\n"," Shu104_Koch169_04b5e404-230b-45e5-ab50-736989230c19.json\n"," Sibyl335_Bernier607_6f1c5c00-112e-4bcd-ae37-388e6552e10e.json\n"," Sirena316_McClure239_fd79b91b-5016-4053-82d8-5cb52a533380.json\n"," Sofia418_Mata817_e026fc6f-e39a-4c89-91bb-e8b81bb46c7c.json\n"," Sondra191_Gislason620_c0b387e4-9a58-4a03-9e98-cdd99f839d4f.json\n"," Suk497_Hermann103_d8a5ea0e-e2af-4ac2-b9b7-a8ff4c828ab0.json\n"," Tabetha269_Legros616_2d49dda8-fef8-492d-aa8e-0e9d382c1f1d.json\n"," Tambra47_Lang846_ae6b9280-f98d-455b-87fa-cc576ab01d2d.json\n"," Tamekia382_Larson43_80cc0c70-806c-4f8b-9b19-09fc0d40ea43.json\n"," Taren286_Zulauf375_ba58d4a4-72fd-41e1-afda-cead75410658.json\n"," Terrilyn343_Barrows492_8f66ad1f-9767-41ed-8de8-a9a8da99ad3c.json\n"," Tiny880_Legros616_a0c65a8f-ef0a-44bc-919b-7288d1e443f1.json\n"," Tonisha838_Steuber698_a105f929-1af0-41e8-80b2-28239c56c519.json\n"," Tory770_DuBuque211_42627ef0-ea02-4323-8059-c8dfb6125314.json\n"," Tula326_Ward668_e74a3332-2b54-4806-b8fb-d750005cefdd.json\n"," Verlene883_Lang846_e10ec25a-1a5c-4b60-9a2d-110f276c25ee.json\n"," Veronique514_Koepp521_874cbeae-3145-40a1-940a-b5fed8a60f99.json\n"," Vivian245_Dach178_37fd5091-034d-40d1-9d85-252c8b399c13.json\n"," Wava789_Corwin846_1e208b6b-77f1-4808-a32b-9f9caf1ec334.json\n"," Xenia801_Adams676_ccef190b-3282-47a3-8a38-be111c4ab299.json\n"," Yael855_Stroman228_6fa5f169-73e1-4921-bf34-4bd08f350e88.json\n"," Yasmin241_Maggio310_1a1a8552-2654-46c0-9f26-f92f7010e923.json\n"," Yetta429_Dibbert990_ffd2246e-31c3-4cd3-99ed-62328029fa0d.json\n"," Ying817_Cole117_2317abf3-9bee-481e-82c3-524456d1ec2b.json\n"]}]},{"cell_type":"code","source":["import json\n","from collections import defaultdict\n","import pandas as pd\n","\n","# Load the JSON file to extract information\n","with open(\"/content/drive/MyDrive/synthea_dataset/Paulita78_Watsica258_2dcefbbe-9f7c-4253-85f8-e1f0e74d90c1.json\") as f:\n","    data = json.load(f)\n","\n","patient={}\n","\n","# Extract the entries\n","entries = data.get('entry', [])\n","\n","# Group by resourceType\n","resource_dict = {}\n","for entry in entries:\n","    resource = entry.get('resource', {})\n","    resource_type = resource.get('resourceType', 'Unknown')\n","    if resource_type not in resource_dict:\n","        resource_dict[resource_type] = []\n","    resource_dict[resource_type].append(resource)\n"],"metadata":{"id":"q7Z53J8cjiRY","executionInfo":{"status":"ok","timestamp":1722377785728,"user_tz":420,"elapsed":290,"user":{"displayName":"Nainika Reddy","userId":"15989986900907940721"}}},"execution_count":46,"outputs":[]},{"cell_type":"code","source":["def flatten_dataframe(df):\n","    for column in df.columns:\n","        if df[column].apply(lambda x: isinstance(x, (list, dict))).any():\n","            # Normalize the nested column\n","            normalized_df = pd.json_normalize(df[column].explode().dropna().tolist(), sep='_')\n","            normalized_df.columns = [f\"{column}_{sub_col}\" for sub_col in normalized_df.columns]\n","            # Drop the original nested column and join the normalized columns\n","            df = df.drop(columns=[column]).join(normalized_df)\n","    return df\n"],"metadata":{"id":"qTAtcRbgcj2D","executionInfo":{"status":"ok","timestamp":1722377785728,"user_tz":420,"elapsed":13,"user":{"displayName":"Nainika Reddy","userId":"15989986900907940721"}}},"execution_count":47,"outputs":[]},{"cell_type":"code","source":["print(resource_dict.keys())"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Lsd5ONw6Ir8U","executionInfo":{"status":"ok","timestamp":1722377785728,"user_tz":420,"elapsed":12,"user":{"displayName":"Nainika Reddy","userId":"15989986900907940721"}},"outputId":"e92663cf-893a-4eec-e324-eef407f152c5"},"execution_count":48,"outputs":[{"output_type":"stream","name":"stdout","text":["dict_keys(['Patient', 'Location', 'Organization', 'Practitioner', 'PractitionerRole', 'Encounter', 'Observation', 'Procedure', 'DiagnosticReport', 'DocumentReference', 'Immunization', 'Condition', 'MedicationRequest', 'CareTeam', 'CarePlan'])\n"]}]},{"cell_type":"code","source":["for resource_type, resources in resource_dict.items():\n","    print(f\"ResourceType: {resource_type}\")\n","    # Normalize the entire resource dictionary and separate nested tags\n","    df = pd.json_normalize(resources, sep='_')\n","    #print(df.columns)\n","\n","    # Flatten the nested columns\n","    df = flatten_dataframe(df)\n","\n","    # Filter out inactive patient information\n","    if 'status' in df.columns:\n","      print(df['status'].unique())\n","        #df = df[(df['status'] == 'active') | (df['status'] == 'current') | (df['status'] == 'final') | (df['status'] == 'finished') | (df['status'] == 'completed')]\n","\n","    if 'id' in df.columns:\n","        df = df.drop(columns=['id'])\n","\n","    columns_to_drop = [col for col in df.columns if any(substring in col for substring in ['reference', 'system', 'telecom', 'identifier', 'Identifier', 'uid', 'Address', 'address'])]\n","    df = df.drop(columns=columns_to_drop)\n","\n","    df = flatten_dataframe(df) #handle second layer of nesting\n","\n","    print(df.columns)\n","    #print(df.head(2))\n","\n","    patient[resource_type] = df\n","    print('\\n')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"dErE6dX6X7_v","executionInfo":{"status":"ok","timestamp":1722377786174,"user_tz":420,"elapsed":456,"user":{"displayName":"Nainika Reddy","userId":"15989986900907940721"}},"outputId":"4a7914cc-3ed6-4447-a448-7c289e7528d0"},"execution_count":49,"outputs":[{"output_type":"stream","name":"stdout","text":["ResourceType: Patient\n","Index(['resourceType', 'gender', 'birthDate', 'multipleBirthBoolean',\n","       'text_status', 'text_div', 'maritalStatus_text', 'extension_url',\n","       'extension_valueString', 'extension_valueCode',\n","       'extension_valueDecimal', 'name_use', 'name_family',\n","       'communication_language_text', 'maritalStatus_coding_code',\n","       'maritalStatus_coding_display', 'extension_extension_url',\n","       'extension_extension_valueCoding_system',\n","       'extension_extension_valueCoding_code',\n","       'extension_extension_valueCoding_display',\n","       'extension_extension_valueString',\n","       'communication_language_coding_system',\n","       'communication_language_coding_code',\n","       'communication_language_coding_display'],\n","      dtype='object')\n","\n","\n","ResourceType: Location\n","['active']\n","Index(['resourceType', 'status', 'name', 'position_longitude',\n","       'position_latitude', 'managingOrganization_display'],\n","      dtype='object')\n","\n","\n","ResourceType: Organization\n","Index(['resourceType', 'active', 'name', 'type_text', 'type_coding_system',\n","       'type_coding_code', 'type_coding_display'],\n","      dtype='object')\n","\n","\n","ResourceType: Practitioner\n","Index(['resourceType', 'active', 'gender', 'name_family'], dtype='object')\n","\n","\n","ResourceType: PractitionerRole\n","Index(['resourceType', 'practitioner_display', 'organization_display',\n","       'code_text', 'specialty_text', 'location_display', 'code_coding_system',\n","       'code_coding_code', 'code_coding_display', 'specialty_coding_system',\n","       'specialty_coding_code', 'specialty_coding_display'],\n","      dtype='object')\n","\n","\n","ResourceType: Encounter\n","['finished']\n","Index(['resourceType', 'status', 'class_code', 'subject_display',\n","       'period_start', 'period_end', 'serviceProvider_display', 'type_text',\n","       'participant_period_start', 'participant_period_end',\n","       'participant_individual_display', 'location_location_display',\n","       'type_coding_system', 'type_coding_code', 'type_coding_display',\n","       'participant_type_coding', 'participant_type_text',\n","       'reasonCode_coding_system', 'reasonCode_coding_code',\n","       'reasonCode_coding_display'],\n","      dtype='object')\n","\n","\n","ResourceType: Observation\n","['final']\n","Index(['resourceType', 'status', 'effectiveDateTime', 'issued', 'code_text',\n","       'valueQuantity_value', 'valueQuantity_unit', 'valueQuantity_code',\n","       'valueCodeableConcept_text', 'code_coding_code', 'code_coding_display',\n","       'component_code_text', 'component_valueQuantity_value',\n","       'component_valueQuantity_unit', 'component_valueQuantity_code',\n","       'valueCodeableConcept_coding_code',\n","       'valueCodeableConcept_coding_display', 'category_coding_system',\n","       'category_coding_code', 'category_coding_display',\n","       'component_code_coding_system', 'component_code_coding_code',\n","       'component_code_coding_display'],\n","      dtype='object')\n","\n","\n","ResourceType: Procedure\n","['completed']\n","Index(['resourceType', 'status', 'code_text', 'performedPeriod_start',\n","       'performedPeriod_end', 'location_display', 'code_coding_code',\n","       'code_coding_display', 'reasonReference_display'],\n","      dtype='object')\n","\n","\n","ResourceType: DiagnosticReport\n","['final']\n","Index(['resourceType', 'status', 'effectiveDateTime', 'issued', 'code_text',\n","       'performer_display', 'result_display', 'code_coding_code',\n","       'code_coding_display', 'presentedForm_contentType',\n","       'presentedForm_data', 'category_coding_system', 'category_coding_code',\n","       'category_coding_display'],\n","      dtype='object')\n","\n","\n","ResourceType: DocumentReference\n","['superseded' 'current']\n","Index(['resourceType', 'status', 'date', 'custodian_display',\n","       'context_period_start', 'context_period_end', 'author_display',\n","       'content_attachment_contentType', 'content_attachment_data',\n","       'content_format_code', 'content_format_display', 'type_coding_code',\n","       'type_coding_display', 'category_coding_system', 'category_coding_code',\n","       'category_coding_display'],\n","      dtype='object')\n","\n","\n","ResourceType: Immunization\n","['completed']\n","Index(['resourceType', 'status', 'occurrenceDateTime', 'primarySource',\n","       'vaccineCode_text', 'location_display', 'vaccineCode_coding_code',\n","       'vaccineCode_coding_display'],\n","      dtype='object')\n","\n","\n","ResourceType: Condition\n","Index(['resourceType', 'onsetDateTime', 'abatementDateTime', 'recordedDate',\n","       'code_text', 'clinicalStatus_coding_code',\n","       'verificationStatus_coding_code', 'code_coding_code',\n","       'code_coding_display', 'stage_summary_text', 'category_coding_system',\n","       'category_coding_code', 'category_coding_display',\n","       'stage_assessment_reference', 'stage_type_coding_system',\n","       'stage_type_coding_code', 'stage_type_coding_display',\n","       'stage_summary_coding_system', 'stage_summary_coding_code',\n","       'stage_summary_coding_display'],\n","      dtype='object')\n","\n","\n","ResourceType: MedicationRequest\n","['completed']\n","Index(['resourceType', 'status', 'intent', 'authoredOn',\n","       'medicationCodeableConcept_text', 'requester_display',\n","       'medicationCodeableConcept_coding_code',\n","       'medicationCodeableConcept_coding_display'],\n","      dtype='object')\n","\n","\n","ResourceType: CareTeam\n","['inactive']\n","Index(['resourceType', 'status', 'period_start', 'period_end',\n","       'participant_member_display', 'reasonCode_text',\n","       'managingOrganization_display', 'participant_role_coding',\n","       'participant_role_text', 'reasonCode_coding_system',\n","       'reasonCode_coding_code', 'reasonCode_coding_display'],\n","      dtype='object')\n","\n","\n","ResourceType: CarePlan\n","['completed']\n","Index(['resourceType', 'status', 'intent', 'text_status', 'text_div',\n","       'period_start', 'period_end', 'category_text',\n","       'activity_detail_code_text', 'activity_detail_status',\n","       'activity_detail_location_display', 'category_coding_system',\n","       'category_coding_code', 'category_coding_display',\n","       'activity_detail_code_coding_system',\n","       'activity_detail_code_coding_code',\n","       'activity_detail_code_coding_display'],\n","      dtype='object')\n","\n","\n"]}]},{"cell_type":"code","source":["for resource_type, resources in resource_dict.items():\n","  print(patient[resource_type].head(2))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"5Yx9YDWNI-Qm","executionInfo":{"status":"ok","timestamp":1722377786447,"user_tz":420,"elapsed":282,"user":{"displayName":"Nainika Reddy","userId":"15989986900907940721"}},"outputId":"069da8a1-e488-4219-894a-ad79d8048b03"},"execution_count":50,"outputs":[{"output_type":"stream","name":"stdout","text":["  resourceType  gender   birthDate  multipleBirthBoolean text_status  \\\n","0      Patient  female  1968-03-10                 False   generated   \n","\n","                                            text_div maritalStatus_text  \\\n","0  <div xmlns=\"http://www.w3.org/1999/xhtml\">Gene...                  M   \n","\n","                                       extension_url extension_valueString  \\\n","0  http://hl7.org/fhir/us/core/StructureDefinitio...                   NaN   \n","\n","  extension_valueCode  ...  maritalStatus_coding_code  \\\n","0                 NaN  ...                          M   \n","\n","  maritalStatus_coding_display extension_extension_url  \\\n","0                            M             ombCategory   \n","\n","  extension_extension_valueCoding_system extension_extension_valueCoding_code  \\\n","0        urn:oid:2.16.840.1.113883.6.238                               2106-3   \n","\n","  extension_extension_valueCoding_display extension_extension_valueString  \\\n","0                                   White                             NaN   \n","\n","  communication_language_coding_system communication_language_coding_code  \\\n","0                      urn:ietf:bcp:47                              en-US   \n","\n","  communication_language_coding_display  \n","0                               English  \n","\n","[1 rows x 24 columns]\n","  resourceType  status                         name  position_longitude  \\\n","0     Location  active  MOUNT HOPE PHYSICAL THERAPY          -71.214181   \n","1     Location  active        SAINT ANNE'S HOSPITAL          -71.094162   \n","\n","   position_latitude managingOrganization_display  \n","0          41.758163  MOUNT HOPE PHYSICAL THERAPY  \n","1          41.725351        SAINT ANNE'S HOSPITAL  \n","   resourceType  active                         name            type_text  \\\n","0  Organization    True  MOUNT HOPE PHYSICAL THERAPY  Healthcare Provider   \n","1  Organization    True        SAINT ANNE'S HOSPITAL  Healthcare Provider   \n","\n","                                  type_coding_system type_coding_code  \\\n","0  http://terminology.hl7.org/CodeSystem/organiza...             prov   \n","1  http://terminology.hl7.org/CodeSystem/organiza...             prov   \n","\n","   type_coding_display  \n","0  Healthcare Provider  \n","1  Healthcare Provider  \n","   resourceType  active gender   name_family\n","0  Practitioner    True   male     Hudson301\n","1  Practitioner    True   male  Cummerata161\n","       resourceType          practitioner_display  \\\n","0  PractitionerRole     Dr. Valentin929 Hudson301   \n","1  PractitionerRole  Dr. Anderson154 Cummerata161   \n","\n","          organization_display         code_text    specialty_text  \\\n","0  MOUNT HOPE PHYSICAL THERAPY  General Practice  General Practice   \n","1        SAINT ANNE'S HOSPITAL  General Practice  General Practice   \n","\n","              location_display                 code_coding_system  \\\n","0  MOUNT HOPE PHYSICAL THERAPY  http://nucc.org/provider-taxonomy   \n","1        SAINT ANNE'S HOSPITAL  http://nucc.org/provider-taxonomy   \n","\n","  code_coding_code code_coding_display            specialty_coding_system  \\\n","0       208D00000X    General Practice  http://nucc.org/provider-taxonomy   \n","1       208D00000X    General Practice  http://nucc.org/provider-taxonomy   \n","\n","  specialty_coding_code specialty_coding_display  \n","0            208D00000X         General Practice  \n","1            208D00000X         General Practice  \n","  resourceType    status class_code            subject_display  \\\n","0    Encounter  finished        AMB  Mrs. Paulita78 Watsica258   \n","1    Encounter  finished        AMB  Mrs. Paulita78 Watsica258   \n","\n","                period_start                 period_end  \\\n","0  1968-03-10T08:49:35-05:00  1968-03-10T09:19:35-05:00   \n","1  1968-04-14T08:49:35-05:00  1968-04-14T09:04:35-05:00   \n","\n","       serviceProvider_display                     type_text  \\\n","0  MOUNT HOPE PHYSICAL THERAPY  Well child visit (procedure)   \n","1  MOUNT HOPE PHYSICAL THERAPY  Well child visit (procedure)   \n","\n","    participant_period_start     participant_period_end  \\\n","0  1968-03-10T08:49:35-05:00  1968-03-10T09:19:35-05:00   \n","1  1968-04-14T08:49:35-05:00  1968-04-14T09:04:35-05:00   \n","\n","  participant_individual_display    location_location_display  \\\n","0      Dr. Valentin929 Hudson301  MOUNT HOPE PHYSICAL THERAPY   \n","1      Dr. Valentin929 Hudson301  MOUNT HOPE PHYSICAL THERAPY   \n","\n","       type_coding_system type_coding_code           type_coding_display  \\\n","0  http://snomed.info/sct        410620009  Well child visit (procedure)   \n","1  http://snomed.info/sct        410620009  Well child visit (procedure)   \n","\n","                             participant_type_coding participant_type_text  \\\n","0  [{'system': 'http://terminology.hl7.org/CodeSy...     primary performer   \n","1  [{'system': 'http://terminology.hl7.org/CodeSy...     primary performer   \n","\n","  reasonCode_coding_system reasonCode_coding_code  \\\n","0   http://snomed.info/sct              195662009   \n","1   http://snomed.info/sct               10509002   \n","\n","            reasonCode_coding_display  \n","0  Acute viral pharyngitis (disorder)  \n","1         Acute bronchitis (disorder)  \n","  resourceType status          effectiveDateTime  \\\n","0  Observation  final  1968-03-10T08:49:35-05:00   \n","1  Observation  final  1968-03-10T08:49:35-05:00   \n","\n","                          issued  \\\n","0  1968-03-10T08:49:35.715-05:00   \n","1  1968-03-10T08:49:35.715-05:00   \n","\n","                                           code_text  valueQuantity_value  \\\n","0                                        Body Height                 48.9   \n","1  Pain severity - 0-10 verbal numeric rating [Sc...                  2.0   \n","\n","  valueQuantity_unit valueQuantity_code valueCodeableConcept_text  \\\n","0                 cm                 cm                       NaN   \n","1            {score}            {score}                       NaN   \n","\n","  code_coding_code  ... component_valueQuantity_unit  \\\n","0           8302-2  ...                       mm[Hg]   \n","1          72514-3  ...                       mm[Hg]   \n","\n","  component_valueQuantity_code  valueCodeableConcept_coding_code  \\\n","0                       mm[Hg]                         266919005   \n","1                       mm[Hg]                         266919005   \n","\n","  valueCodeableConcept_coding_display  \\\n","0      Never smoked tobacco (finding)   \n","1      Never smoked tobacco (finding)   \n","\n","                              category_coding_system category_coding_code  \\\n","0  http://terminology.hl7.org/CodeSystem/observat...          vital-signs   \n","1  http://terminology.hl7.org/CodeSystem/observat...          vital-signs   \n","\n","  category_coding_display component_code_coding_system  \\\n","0             vital-signs             http://loinc.org   \n","1             vital-signs             http://loinc.org   \n","\n","  component_code_coding_code component_code_coding_display  \n","0                     8462-4      Diastolic Blood Pressure  \n","1                     8480-6       Systolic Blood Pressure  \n","\n","[2 rows x 23 columns]\n","  resourceType     status                              code_text  \\\n","0    Procedure  completed  Medication Reconciliation (procedure)   \n","1    Procedure  completed  Medication Reconciliation (procedure)   \n","\n","       performedPeriod_start        performedPeriod_end  \\\n","0  1968-03-10T08:49:35-05:00  1968-03-10T09:04:35-05:00   \n","1  1968-06-16T09:49:35-04:00  1968-06-16T10:04:35-04:00   \n","\n","              location_display code_coding_code  \\\n","0  MOUNT HOPE PHYSICAL THERAPY        430193006   \n","1  MOUNT HOPE PHYSICAL THERAPY        430193006   \n","\n","                     code_coding_display             reasonReference_display  \n","0  Medication Reconciliation (procedure)  Acute viral pharyngitis (disorder)  \n","1  Medication Reconciliation (procedure)                   Facial laceration  \n","       resourceType status          effectiveDateTime  \\\n","0  DiagnosticReport  final  1968-03-10T08:49:35-05:00   \n","1  DiagnosticReport  final  1968-03-10T08:49:35-05:00   \n","\n","                          issued  \\\n","0  1968-03-10T08:49:35.715-05:00   \n","1  1968-03-10T08:49:35.715-05:00   \n","\n","                                           code_text  \\\n","0  Complete blood count (hemogram) panel - Blood ...   \n","1                                                NaN   \n","\n","             performer_display  \\\n","0  MOUNT HOPE PHYSICAL THERAPY   \n","1    Dr. Valentin929 Hudson301   \n","\n","                                      result_display code_coding_code  \\\n","0  Leukocytes [#/volume] in Blood by Automated count          58410-2   \n","1  Erythrocytes [#/volume] in Blood by Automated ...          34117-2   \n","\n","                                 code_coding_display  \\\n","0  Complete blood count (hemogram) panel - Blood ...   \n","1                          History and physical note   \n","\n","  presentedForm_contentType  \\\n","0                text/plain   \n","1                text/plain   \n","\n","                                  presentedForm_data  \\\n","0  CjE5NjgtMDMtMTAKCiMgQ2hpZWYgQ29tcGxhaW50Ck5vIG...   \n","1  CjE5NjgtMDQtMTQKCiMgQ2hpZWYgQ29tcGxhaW50Ck5vIG...   \n","\n","                          category_coding_system category_coding_code  \\\n","0  http://terminology.hl7.org/CodeSystem/v2-0074                  LAB   \n","1                               http://loinc.org              34117-2   \n","\n","     category_coding_display  \n","0                 Laboratory  \n","1  History and physical note  \n","        resourceType      status                           date  \\\n","0  DocumentReference  superseded  1968-03-10T08:49:35.715-05:00   \n","1  DocumentReference  superseded  1968-04-14T08:49:35.715-05:00   \n","\n","             custodian_display       context_period_start  \\\n","0  MOUNT HOPE PHYSICAL THERAPY  1968-03-10T08:49:35-05:00   \n","1  MOUNT HOPE PHYSICAL THERAPY  1968-04-14T08:49:35-05:00   \n","\n","          context_period_end             author_display  \\\n","0  1968-03-10T09:19:35-05:00  Dr. Valentin929 Hudson301   \n","1  1968-04-14T09:04:35-05:00  Dr. Valentin929 Hudson301   \n","\n","  content_attachment_contentType  \\\n","0         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                          participant_role_coding  \\\n","0  [{'system': 'http://snomed.info/sct', 'code': ...   \n","1  [{'system': 'http://snomed.info/sct', 'code': ...   \n","\n","                  participant_role_text reasonCode_coding_system  \\\n","0                               Patient   http://snomed.info/sct   \n","1  Healthcare professional (occupation)   http://snomed.info/sct   \n","\n","  reasonCode_coding_code    reasonCode_coding_display  \n","0              370247008            Facial laceration  \n","1               10509002  Acute bronchitis (disorder)  \n","  resourceType     status intent text_status  \\\n","0     CarePlan  completed  order   generated   \n","1     CarePlan  completed  order   generated   \n","\n","                                            text_div  \\\n","0  <div xmlns=\"http://www.w3.org/1999/xhtml\">Care...   \n","1  <div xmlns=\"http://www.w3.org/1999/xhtml\">Care...   \n","\n","                period_start                 period_end category_text  \\\n","0  1970-01-29T08:49:35-05:00  1970-02-12T08:49:35-05:00           NaN   \n","1  1973-05-14T09:49:35-04:00  1974-02-24T09:49:35-04:00    Wound care   \n","\n","       activity_detail_code_text activity_detail_status  \\\n","0     Dressing change management              completed   \n","1  Behavior to prevent infection              completed   \n","\n","  activity_detail_location_display  \\\n","0            SAINT ANNE'S HOSPITAL   \n","1            SAINT ANNE'S HOSPITAL   \n","\n","                              category_coding_system category_coding_code  \\\n","0  http://hl7.org/fhir/us/core/CodeSystem/carepla...          assess-plan   \n","1                             http://snomed.info/sct            225358003   \n","\n","  category_coding_display activity_detail_code_coding_system  \\\n","0                     NaN             http://snomed.info/sct   \n","1              Wound care             http://snomed.info/sct   \n","\n","  activity_detail_code_coding_code activity_detail_code_coding_display  \n","0                        385949008          Dressing change management  \n","1                        439830001       Behavior to prevent infection  \n"]}]},{"cell_type":"code","source":["import requests\n","import pandas as pd\n","\n","# Initial URL for the first API call\n","base_url = \"https://clinicaltrials.gov/api/v2/studies\"\n","params = {\n","    \"query.titles\": \"Breast Cancer\",\n","    \"pageSize\": 100\n","}\n","\n","# Initialize an empty list to store the data\n","data_list = []\n","\n","# Loop until there is no nextPageToken\n","while True:\n","    # Print the current URL (for debugging purposes)\n","    print(\"Fetching data from:\", base_url + '?' + '&'.join([f\"{k}={v}\" for k, v in params.items()]))\n","\n","    # Send a GET request to the API\n","    response = requests.get(base_url, params=params)\n","\n","    # Check if the request was successful\n","    if response.status_code == 200:\n","        data = response.json()  # Parse JSON response\n","        studies = data.get('studies', [])  # Extract the list of studies\n","\n","        # Loop through each study and extract specific information\n","        for study in studies:\n","            # Safely access nested keys\n","            nctId = study['protocolSection']['identificationModule'].get('nctId', 'Unknown')\n","            overallStatus = study['protocolSection']['statusModule'].get('overallStatus', 'Unknown')\n","            startDate = study['protocolSection']['statusModule'].get('startDateStruct', {}).get('date', 'Unknown Date')\n","            conditions = ', '.join(study['protocolSection']['conditionsModule'].get('conditions', ['No conditions listed']))\n","            acronym = study['protocolSection']['identificationModule'].get('acronym', 'Unknown')\n","\n","            # Extract interventions safely\n","            interventions_list = study['protocolSection'].get('armsInterventionsModule', {}).get('interventions', [])\n","            interventions = ', '.join([intervention.get('name', 'No intervention name listed') for intervention in interventions_list]) if interventions_list else \"No interventions listed\"\n","\n","            # Extract locations safely\n","            locations_list = study['protocolSection'].get('contactsLocationsModule', {}).get('locations', [])\n","            locations = ', '.join([f\"{location.get('city', 'No City')} - {location.get('country', 'No Country')}\" for location in locations_list]) if locations_list else \"No locations listed\"\n","\n","            # Extract dates and phases\n","            primaryCompletionDate = study['protocolSection']['statusModule'].get('primaryCompletionDateStruct', {}).get('date', 'Unknown Date')\n","            studyFirstPostDate = study['protocolSection']['statusModule'].get('studyFirstPostDateStruct', {}).get('date', 'Unknown Date')\n","            lastUpdatePostDate = study['protocolSection']['statusModule'].get('lastUpdatePostDateStruct', {}).get('date', 'Unknown Date')\n","            studyType = study['protocolSection']['designModule'].get('studyType', 'Unknown')\n","            phases = ', '.join(study['protocolSection']['designModule'].get('phases', ['Not Available']))\n","\n","            # Extract eligibility criteria\n","            #eligibilities = ', '.join(study['protocolSection']['eligibilityModule'].get('eligibilityCriteria', ['No criteria listed']))\n","\n","            eligibility = study['protocolSection']['eligibilityModule'].get('eligibilityCriteria', 'Unknown')\n","\n","            #eligibilities_list = study['protocolSection'].get('eligibilityModule', {}).get('eligibilityCriteria', [])\n","            #eligibilities = ', '.join([eligiblity.get('name', 'No criteria listed') for eligiblity in eligibilities_list]) if eligibilities_list else \"No eligibility listed\"\n","\n","            # Append the data to the list as a dictionary\n","            data_list.append({\n","                \"NCT ID\": nctId,\n","                \"Acronym\": acronym,\n","                \"Overall Status\": overallStatus,\n","                \"Start Date\": startDate,\n","                \"Conditions\": conditions,\n","                \"Interventions\": interventions,\n","                \"Locations\": locations,\n","                \"Primary Completion Date\": primaryCompletionDate,\n","                \"Study First Post Date\": studyFirstPostDate,\n","                \"Last Update Post Date\": lastUpdatePostDate,\n","                \"Study Type\": studyType,\n","                \"Phases\": phases,\n","                \"Eligibility\": eligibility\n","            })\n","\n","        # Check for nextPageToken and update the params or break the loop\n","        nextPageToken = data.get('nextPageToken')\n","        if nextPageToken:\n","            params['pageToken'] = nextPageToken  # Set the pageToken for the next request\n","        else:\n","            break  # Exit the loop if no nextPageToken is present\n","    else:\n","        print(\"Failed to fetch data. Status code:\", response.status_code)\n","        break\n","\n","# Create a DataFrame from the list of dictionaries\n","clinical_trials_data = pd.DataFrame(data_list)\n","\n","# Print the DataFrame\n","#print(clinical_trials_data)\n","\n","# Optionally, save the DataFrame to a CSV file\n","clinical_trials_data.to_csv(\"clinical_trials_data.csv\", index=False)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"80IwH-bMvdV_","executionInfo":{"status":"ok","timestamp":1722377817971,"user_tz":420,"elapsed":31529,"user":{"displayName":"Nainika Reddy","userId":"15989986900907940721"}},"outputId":"9e62ae6c-188e-47fe-c46f-6441e41290a6"},"execution_count":51,"outputs":[{"output_type":"stream","name":"stdout","text":["Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JeHkvIv\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JWPm_cp\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKHlPQoyA\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKDkPApxQ\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKBlfEsww\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JGHk_MtwA\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JGEl_cqwA\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JGBlPYrwg\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JCHlfQuxg\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JCDkPMtxA\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JCAkfIqyQ\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JeGk_UtwQ\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JeDlPgqxQ\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JeAlPgpww\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JaHlvIpxA\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JaElPYgyA\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JaBlvUuxg\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JaOkfMpww\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JWFl_ktxw\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JWBlPkhwA\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JSHk_YvyA\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JSDk_QgyQ\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JSAm_Ipww\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JuGkPAswA\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JuDm_khwg\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JuPkfgvww\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JqGlPEgyA\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JqCkfggxQ\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JqPlvQgyA\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKHkPMrww4\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKHl_guwAA\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKHm_gqwAY\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKGkfAuwAU\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKGlPQgyQ8\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKGm_cgwgA\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKFkPYqwQM\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKFlPEvxg4\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKFmvYsxg8\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKEkPQgxwY\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKElPAuxAM\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKDkvMrxQU\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKDkfYryA8\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKDlfMsxgY\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKCkvcvyA4\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKClvQqyQU\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKClPghxAQ\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKBkvAvxg8\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKBkPkhxgM\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKBlfEtxAY\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKAkvMtxQc\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKAkfIqxA4\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKAlPkswAc\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKPkvQqwwI\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKPkfQoxwc\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKPlPgtwQc\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKPm_YqxQI\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKOkPcsxg8\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKOl_YtxwA\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JKOm_IgwAA\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JGHkfMtxwM\n","Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=Breast Cancer&pageSize=100&pageToken=NF0g5JGHl_gpwgM\n","Fetching data from: 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'sk-proj-XIZYSWf9cabLNiQ4h9HvT3BlbkFJZXRUtBkclFgKigJ7WHuH' # go to platform.openai.com to find your key!\n","os.environ[\"OPENAI_API_KEY\"] = 'sk-proj-bbcCqgJsIPOhjmiRfNdyT3BlbkFJuDf9IePweh97i2lYZkTl' # API Key from Jieming for MVP\n","# model\n","model = \"gpt-4-turbo\" # most powerful gpt model\n","llm = ChatOpenAI(temperature=0.1, model=model)"],"metadata":{"id":"P-eCyerOvtxo","executionInfo":{"status":"ok","timestamp":1722377825470,"user_tz":420,"elapsed":8,"user":{"displayName":"Nainika Reddy","userId":"15989986900907940721"}}},"execution_count":55,"outputs":[]},{"cell_type":"code","source":["from openai import OpenAI\n","\n","client = OpenAI(\n","  api_key=os.environ[\"OPENAI_API_KEY\"],  # this is also the default, it can be omitted\n",")"],"metadata":{"id":"0nKiUoHBvyF9","executionInfo":{"status":"ok","timestamp":1722377825470,"user_tz":420,"elapsed":6,"user":{"displayName":"Nainika Reddy","userId":"15989986900907940721"}}},"execution_count":56,"outputs":[]},{"cell_type":"markdown","source":["### **Part 1:** Querying the LLM with the full health record and the full clinical trials dataframe."],"metadata":{"id":"N4SoKzv6EzUt"}},{"cell_type":"code","source":["from datetime import date\n","today_date = date.today()"],"metadata":{"id":"OZHT8xWuq9CB","executionInfo":{"status":"ok","timestamp":1722377825693,"user_tz":420,"elapsed":228,"user":{"displayName":"Nainika Reddy","userId":"15989986900907940721"}}},"execution_count":57,"outputs":[]},{"cell_type":"code","source":["query = f\"\"\"You are a doctor seeing a patient diagnosed with a type of breast cancer with the following medical history. {patient}. Extract information about the patient's cancer prognosis and treatment. The patient's age can be inferred from today's data, {today_date} and the patient’s date of birth. Use this information and the clinical trial inclusion/exclusion criteria to identify up to 4 clinical trials that the patient is eligible for. The patient must meet all of the criteria listed for the clinical trial. Identify and report the NCT ID number and the clinical trial eligibility criteria. List four reasons why the patient is eligible for each trial. If the patient does not match the criteria for any of the trials, explain why.{clinical_trials_data}'\n","\"\"\"\n","\n","#print(query)\n","\n","response = llm.invoke(query)"],"metadata":{"id":"oJdyfY391k2m","executionInfo":{"status":"ok","timestamp":1722377852897,"user_tz":420,"elapsed":27207,"user":{"displayName":"Nainika Reddy","userId":"15989986900907940721"}}},"execution_count":58,"outputs":[]},{"cell_type":"code","source":["print(response.content)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"F0LGXamtNsrh","executionInfo":{"status":"ok","timestamp":1722377852898,"user_tz":420,"elapsed":19,"user":{"displayName":"Nainika Reddy","userId":"15989986900907940721"}},"outputId":"56d21d69-572d-4747-9bf5-a571ca81bc4f"},"execution_count":59,"outputs":[{"output_type":"stream","name":"stdout","text":["Based on the provided data, the patient is a female born on March 10, 1968, which makes her 56 years old as of today's date, July 30, 2024. She has been diagnosed with a type of breast cancer, specifically \"Malignant neoplasm of breast (disorder).\" To find suitable clinical trials for her, we need to consider her age, gender, cancer type, and stage, along with other specific eligibility criteria mentioned in the trials.\n","\n","From the clinical trials data snippet you provided, I will analyze the eligibility criteria for each trial to determine if the patient qualifies. Here are four clinical trials that the patient might be eligible for, based on the information available:\n","\n","### Clinical Trial 1: NCT06155331\n","- **Eligibility Criteria:**\n","  - Age ≥ 18 years old.\n","  - Diagnosed with stage 2 or 3 breast cancer.\n","  - Requires chemotherapy.\n","  - No prior treatment for the current cancer diagnosis.\n","\n","**Reasons for Eligibility:**\n","1. The patient is 56 years old, meeting the age criterion.\n","2. She has breast cancer, although the exact stage isn't specified in the data provided; further investigation is needed to confirm the stage.\n","3. The patient's medical history does not mention prior treatment for the current cancer, aligning with the trial's requirement.\n","4. The trial is actively recruiting, which means the patient can potentially participate if other medical conditions align.\n","\n","### Clinical Trial 2: NCT04603820\n","- **Eligibility Criteria:**\n","  - The patient should have a diagnosis of breast cancer.\n","  - The patient is pregnant or within one year post-partum.\n","  - Willing to provide medical information related to pregnancy and cancer treatment.\n","\n","**Reasons for Eligibility:**\n","1. The patient has a diagnosis of breast cancer.\n","2. Additional details about her current pregnancy status are required to fully confirm eligibility.\n","3. The trial focuses on the interaction of pregnancy and breast cancer treatment, which might be relevant if the patient is pregnant or was recently.\n","4. This observational study could provide valuable insights into her condition during or after pregnancy.\n","\n","### Clinical Trial 3: NCT04074720\n","- **Eligibility Criteria:**\n","  - Adults >18 years old.\n","  - Diagnosed with invasive breast cancer.\n","  - Able to provide consent.\n","  - No other concurrent malignancies.\n","\n","**Reasons for Eligibility:**\n","1. The patient is over 18 years old.\n","2. She has a diagnosis of breast cancer, specified as malignant neoplasm which is invasive.\n","3. There is no mention of other concurrent malignancies in her medical history.\n","4. The patient can provide consent if mentally competent.\n","\n","### Clinical Trial 4: NCT06087120\n","- **Eligibility Criteria:**\n","  - Female, 18 years old and above.\n","  - Diagnosed with stage II or III breast cancer.\n","  - No prior chemotherapy for the current cancer.\n","  - Willing to undergo specific treatments listed in the trial.\n","\n","**Reasons for Eligibility:**\n","1. The patient is female and above 18 years old.\n","2. She has breast cancer, pending confirmation of the specific stage.\n","3. No prior chemotherapy for the current cancer is mentioned in her history.\n","4. Assuming she is willing, she can participate in the treatments required by the trial.\n","\n","**Note:** For each of these trials, further medical evaluation and detailed information about her current health status, cancer stage, and treatment history are crucial to confirm eligibility. The patient should discuss potential participation with her oncologist, who can provide a more detailed assessment and facilitate the application to these trials if she meets all the criteria.\n"]}]},{"cell_type":"markdown","source":["### **Part 2:** Prompt the LLM to write a patient summary, given a full health record."],"metadata":{"id":"NUoc33uqVkzy"}},{"cell_type":"markdown","source":["#### Summary 1"],"metadata":{"id":"V2Gp6y1-V8ez"}},{"cell_type":"code","source":["query = f\"\"\"You are a doctor seeing a patient diagnosed with a type of breast cancer with the following health record in the mCODE format. Write a summary for this patient's cancer prognosis. {patient}'\n","\"\"\"\n","\n","response = llm.invoke(query)\n","\n","print(response.content)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Ri9e5l2s_qyt","executionInfo":{"status":"ok","timestamp":1722377867260,"user_tz":420,"elapsed":14371,"user":{"displayName":"Nainika Reddy","userId":"15989986900907940721"}},"outputId":"be57095a-6a02-4ad6-bd85-7a2afa666c5b"},"execution_count":60,"outputs":[{"output_type":"stream","name":"stdout","text":["The patient, Mrs. Paulita78 Watsica258, has been diagnosed with malignant neoplasm of the breast (breast cancer). The diagnosis was recorded on February 26, 2020. The clinical status of the condition is active, and it has been confirmed. The specific type of breast cancer, based on the SNOMED code provided (254837009), indicates a diagnosis of malignant neoplasm of the breast without further specification of the subtype.\n","\n","The patient's care has been managed by various healthcare providers, including Dr. Anderson154 Cummerata161 and Dr. Dominique369 Crist667, with encounters primarily at Saint Anne's Hospital. The patient has a history of various conditions and treatments, including acute bronchitis, viral pharyngitis, and procedures like medication reconciliation and radiation therapy.\n","\n","Given the active status of the breast cancer, ongoing treatment and monitoring are critical. The patient's prognosis will depend on several factors, including the stage of cancer at diagnosis, the specific characteristics of the tumor, response to treatment, and overall health condition. Regular follow-ups and adherence to the treatment plan are essential for managing the condition effectively.\n","\n","The patient's medical history also includes other conditions such as obesity and a history of normal pregnancies and complications like antepartum eclampsia. These factors may influence the overall management plan for her breast cancer.\n","\n","It is recommended to continue with a comprehensive care plan that includes regular medical reviews, continued cancer treatment as per oncology guidelines, and supportive care to manage symptoms and improve quality of life. The care team should also consider the patient's past medical history and current health status in managing her treatment plan effectively.\n"]}]},{"cell_type":"markdown","source":["#### Summary 2"],"metadata":{"id":"6YH4CglpWEW7"}},{"cell_type":"code","source":["query = f\"\"\"You are a doctor seeing a patient diagnosed with a type of breast cancer with the following health record in the mCODE format. Write a detailed summary for this patient's cancer diagnosis and prognosis. Report the clinical stage type of the cancer diagnosis and other descriptive information about the cancer. Report the gender and the patient's age as of today's date, {today_date}. Report the patient's comorbidities and treatments. {patient}'\n","\"\"\"\n","\n","response = llm.invoke(query)\n","\n","print(response.content)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"bGhku4WUJGfQ","executionInfo":{"status":"ok","timestamp":1722377886341,"user_tz":420,"elapsed":19086,"user":{"displayName":"Nainika Reddy","userId":"15989986900907940721"}},"outputId":"3fc936af-c280-429a-f681-fd63d3f86974"},"execution_count":61,"outputs":[{"output_type":"stream","name":"stdout","text":["### Patient Summary\n","\n","**Patient Details:**\n","- **Name:** Mrs. Paulita78 Watsica258\n","- **Gender:** Female\n","- **Date of Birth:** March 10, 1968\n","- **Age:** 56 years old (as of today's date, July 30, 2024)\n","- **Marital Status:** Married\n","- **Race:** White\n","- **Primary Language:** English\n","\n","**Medical History and Comorbidities:**\n","- Mrs. Watsica has a history of various acute conditions such as acute viral pharyngitis, acute bronchitis, and otitis media. She has also experienced facial laceration, epidermal burn, and normal pregnancies. Notably, she has been diagnosed with a malignant neoplasm of the breast (breast cancer) as of February 26, 2020.\n","\n","**Cancer Diagnosis:**\n","- **Type of Cancer:** Malignant neoplasm of the breast\n","- **Stage at Diagnosis:** Stage 1A\n","- **Date of Diagnosis:** February 26, 2020\n","- **Clinical Status:** Active\n","- **Verification Status:** Confirmed\n","\n","**Treatment and Care:**\n","- Mrs. Watsica has undergone various treatments and procedures, including radiation therapy care as part of her cancer treatment plan. She has also been prescribed medications like acetaminophen for symptomatic relief of other conditions and has been involved in care plans focusing on respiratory therapy and wound care.\n","\n","**Healthcare Providers and Locations:**\n","- **Primary Care Providers:**\n","  - Dr. Anderson154 Cummerata161\n","  - Dr. Dominique369 Crist667\n","- **Care Locations:**\n","  - Saint Anne's Hospital\n","  - Mount Hope Physical Therapy\n","  - Southcoast Hospital Group, Inc.\n","\n","**Recent Healthcare Encounters:**\n","- Mrs. Watsica has had multiple encounters for problem management at Southcoast Hospital Group, Inc., with the most recent visits focused on managing her breast cancer and associated treatments.\n","\n","**Prognosis:**\n","- Given the early stage of breast cancer at diagnosis (Stage 1A), the prognosis could be cautiously optimistic, depending on her response to treatments, overall health, and absence of significant comorbidities directly impacting her cancer treatment.\n","\n","**Additional Notes:**\n","- Mrs. Watsica has been actively managing her health with regular follow-ups and has been compliant with the treatment regimens prescribed by her healthcare providers. Her care team has been actively involved in her treatment journey, ensuring a multidisciplinary approach to her cancer care and other health concerns.\n"]}]},{"cell_type":"code","source":["patient_summary = response.content"],"metadata":{"id":"uqFi3hjXKlQw","executionInfo":{"status":"ok","timestamp":1722377886341,"user_tz":420,"elapsed":18,"user":{"displayName":"Nainika Reddy","userId":"15989986900907940721"}}},"execution_count":62,"outputs":[]},{"cell_type":"code","source":["print(patient_summary)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"GBWXQmZ6r-bW","executionInfo":{"status":"ok","timestamp":1722377886342,"user_tz":420,"elapsed":14,"user":{"displayName":"Nainika Reddy","userId":"15989986900907940721"}},"outputId":"e4453278-cb07-4a4c-fa85-279fa5964816"},"execution_count":63,"outputs":[{"output_type":"stream","name":"stdout","text":["### Patient Summary\n","\n","**Patient Details:**\n","- **Name:** Mrs. Paulita78 Watsica258\n","- **Gender:** Female\n","- **Date of Birth:** March 10, 1968\n","- **Age:** 56 years old (as of today's date, July 30, 2024)\n","- **Marital Status:** Married\n","- **Race:** White\n","- **Primary Language:** English\n","\n","**Medical History and Comorbidities:**\n","- Mrs. Watsica has a history of various acute conditions such as acute viral pharyngitis, acute bronchitis, and otitis media. She has also experienced facial laceration, epidermal burn, and normal pregnancies. Notably, she has been diagnosed with a malignant neoplasm of the breast (breast cancer) as of February 26, 2020.\n","\n","**Cancer Diagnosis:**\n","- **Type of Cancer:** Malignant neoplasm of the breast\n","- **Stage at Diagnosis:** Stage 1A\n","- **Date of Diagnosis:** February 26, 2020\n","- **Clinical Status:** Active\n","- **Verification Status:** Confirmed\n","\n","**Treatment and Care:**\n","- Mrs. Watsica has undergone various treatments and procedures, including radiation therapy care as part of her cancer treatment plan. She has also been prescribed medications like acetaminophen for symptomatic relief of other conditions and has been involved in care plans focusing on respiratory therapy and wound care.\n","\n","**Healthcare Providers and Locations:**\n","- **Primary Care Providers:**\n","  - Dr. Anderson154 Cummerata161\n","  - Dr. Dominique369 Crist667\n","- **Care Locations:**\n","  - Saint Anne's Hospital\n","  - Mount Hope Physical Therapy\n","  - Southcoast Hospital Group, Inc.\n","\n","**Recent Healthcare Encounters:**\n","- Mrs. Watsica has had multiple encounters for problem management at Southcoast Hospital Group, Inc., with the most recent visits focused on managing her breast cancer and associated treatments.\n","\n","**Prognosis:**\n","- Given the early stage of breast cancer at diagnosis (Stage 1A), the prognosis could be cautiously optimistic, depending on her response to treatments, overall health, and absence of significant comorbidities directly impacting her cancer treatment.\n","\n","**Additional Notes:**\n","- Mrs. Watsica has been actively managing her health with regular follow-ups and has been compliant with the treatment regimens prescribed by her healthcare providers. Her care team has been actively involved in her treatment journey, ensuring a multidisciplinary approach to her cancer care and other health concerns.\n"]}]},{"cell_type":"markdown","source":["### **Part 3:** Querying the LLM with the patient summary and the full clinical trials dataframe."],"metadata":{"id":"L7M3qD8AWgJc"}},{"cell_type":"code","source":["query = f\"\"\"You are a doctor seeing a patient diagnosed with a type of breast cancer with the following medical history. {patient_summary}. Use this information and the clinical trial inclusion/exclusion criteria to identify up to 4 clinical trials that the patient is eligible for. The patient must meet all of the criteria listed for the clinical trial. Identify and report the NCT ID number and the clinical trial eligibility (inclusion and exclusion) criteria. For each eligibility criterion for the trial, explain why the patient is eligible. If the patient does not match the criteria for any of the trials, explain why. {clinical_trials_data}.’\n","\"\"\"\n","\n","response = llm.invoke(query)\n","\n","print(response.content)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"McN4sUZ8WSkF","executionInfo":{"status":"ok","timestamp":1722377910184,"user_tz":420,"elapsed":23853,"user":{"displayName":"Nainika Reddy","userId":"15989986900907940721"}},"outputId":"ad4287c8-8209-4276-9be6-c7b4b17331e9"},"execution_count":64,"outputs":[{"output_type":"stream","name":"stdout","text":["Based on the patient's medical history and the clinical trial information provided, we can evaluate Mrs. Paulita78 Watsica258's eligibility for the listed clinical trials. Here are the assessments for four selected trials:\n","\n","### Trial 1: NCT06155331\n","**Eligibility Criteria:**\n","- Age ≥ 18 years old.\n","- Diagnosed with breast cancer stage 2 or 3.\n","- Able to receive chemotherapy.\n","- No prior treatment with fenofibrate.\n","\n","**Reasons for Ineligibility:**\n","1. **Stage of Cancer:** Mrs. Watsica was diagnosed with Stage 1A breast cancer, which does not meet the trial's requirement for stage 2 or 3 breast cancer.\n","2. **Other criteria match,** but the stage mismatch disqualifies her.\n","\n","### Trial 2: NCT04603820\n","**Eligibility Criteria:**\n","- The patient should have breast cancer and be pregnant.\n","\n","**Reasons for Ineligibility:**\n","1. **Pregnancy Status:** There is no information suggesting that Mrs. Watsica is currently pregnant.\n","2. **Specific Condition Requirement:** The trial specifically requires participants to be pregnant, which is not applicable to Mrs. Watsica.\n","\n","### Trial 3: NCT04074720\n","**Eligibility Criteria:**\n","- Adults >18 years old.\n","- Diagnosed with breast cancer.\n","- Willing to provide tissue and blood samples.\n","\n","**Reasons for Eligibility:**\n","1. **Age:** Mrs. Watsica is 56 years old, meeting the age criterion.\n","2. **Diagnosis:** She has been diagnosed with breast cancer.\n","3. **Consent Capability:** There is no indication that she would be unwilling to provide samples; assuming standard consent, she meets this criterion.\n","4. **General Health:** Her medical history does not indicate any conditions that would preclude her from providing samples.\n","\n","### Trial 4: NCT06087120\n","**Eligibility Criteria:**\n","- Female, 18 years old and above.\n","- Diagnosed with Stage II breast cancer or higher.\n","- Able to participate in the study procedures.\n","\n","**Reasons for Ineligibility:**\n","1. **Stage of Cancer:** Mrs. Watsica's cancer is Stage 1A, which does not meet the requirement for Stage II or higher.\n","2. **Other criteria match,** but the stage requirement is not met.\n","\n","### Conclusion:\n","From the trials evaluated, Mrs. Watsica is only potentially eligible for NCT04074720, which involves tissue and blood sample collection from breast cancer patients. The other trials have specific criteria related to the stage of cancer or other conditions (like pregnancy) that do not match her situation. It is crucial to always verify with the patient about any updates in her condition or treatment that might affect eligibility before proceeding with trial enrollment.\n"]}]},{"cell_type":"markdown","source":["### **Part 4:** Querying the LLM with the patient summary and the clinical trials data using a RAG-enabled approach"],"metadata":{"id":"rB0atWLmXuJ4"}},{"cell_type":"code","source":["clinical_trials_data['text'] = 'The trial with NCT ID number ' + clinical_trials_data['NCT ID'] + ' has the following eligbility criteria, for inclusion and exclusion ' + clinical_trials_data['Eligibility']\n","clinical_trials_data.head()['text']"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":969},"id":"OnaGu23Wy1u5","executionInfo":{"status":"ok","timestamp":1722377910185,"user_tz":420,"elapsed":26,"user":{"displayName":"Nainika Reddy","userId":"15989986900907940721"}},"outputId":"491ad364-4a7d-4f93-87f3-0f453b012778"},"execution_count":65,"outputs":[{"output_type":"execute_result","data":{"text/plain":["14    The trial with NCT ID number NCT06155331 has t...\n","34    The trial with NCT ID number NCT04603820 has t...\n","35    The trial with NCT ID number NCT04074720 has t...\n","38    The trial with NCT ID number NCT06087120 has t...\n","39    The trial with NCT ID number NCT01785420 has t...\n","Name: text, dtype: object"],"text/html":["<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>text</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>14</th>\n","      <td>The trial with NCT ID number NCT06155331 has the following eligbility criteria, for inclusion and exclusion Inclusion Criteria:\\n\\n* Age ≥ 18 years old.\\n* Patients with biopsy confirmed diagnosis breast cancer and with stage II and stage III breast cancer according to the American Joint Committee on Cancer (TNM staging system of breast cancer).\\n* Patients with performance status \\&lt;2 according to Eastern Cooperative Oncology Group (ECOG) score.\\n* Adequate baseline hematologic values (absolute neutrophilic count ≥ 1.5 × 109/L, platelet count ≥ 100 × 109/L and hemoglobin level ≥ 10 g/dl).\\n* Patients with adequate liver function (serum bilirubin \\&lt; 1.2 mg/dl) and adequate renal function (serum creatinine \\&lt; 1.5 mg/d).\\n\\nExclusion Criteria:\\n\\n* Patients with prior exposure to anthracyclines in the last 6 months.\\n* Patients with evidence of metastasis at the initial assessment.\\n* Concomitant use of antioxidant vitamins (vitamin A, C, E).\\n* Presence of clinical evidence for severe cardiac illness (angina pectoris, uncontrolled hypertension, arrhythmias and left ventricular ejection fraction \\&lt;50%).\\n* Patients with inflammatory diseases (ulcerative colitis, rheumatoid arthritis).\\n* Patients with conditions associated with oxidative stress (smoking, tuberculosis, comorbid obesity).\\n* Patients who are candidates for monoclonal antibodies such as Trastuzumab and other targeted therapy (HER2 positive patients).\\n* Patients with active liver disease (cirrhosis, fatty liver, hepatitis C, etc..).\\n* Patients with myopathy.\\n* Patients with renal impairment, including those with end-stage renal disease and those receiving dialysis.\\n* Pregnant and breast feeding women.\\n* Known allergy to the fenofibrates.\\n* Concurrent use of statin, colchicine, ciprofibrate, idelalisib, ivacaftor, aspirin low strength, clopidogrel, warfarin, enzyme inducers (phenytoin, phenobarbitone, carbamazepine,...), enzyme inhibitors (allopurinol, MAOI, SSRI,...), drugs with high plasma protein binding capacity (sulfonamides, valproate, oral hypoglycemic, warfarin,...) in order to avoid potential pharmacodynamics and pharmacokinetic drug interactions.</td>\n","    </tr>\n","    <tr>\n","      <th>34</th>\n","      <td>The trial with NCT ID number NCT04603820 has the following eligbility criteria, for inclusion and exclusion Inclusion Criteria:\\n\\n1. The patient should have signed and dated the informed consent form (ICF). The enrollment of patients who have died is allowed.\\n2. Women aged ≥ 18 years.\\n3. Patients in one of the following situations:\\n\\n   * Patients with breast cancer diagnosis during pregnancy, breastfeeding or within the year after delivery.\\n   * Patients with breast cancer who become pregnant after treatment.\\n   * Patients with breast cancer who were subjected to any fertility preservation method prior to the start of breast cancer treatment.\\n4. The patients referred to in the previous section and the patients who meet these characteristics prospectively could be enrolled retrospectively upon registry opening.\\n5. All cases diagnosed at the same site may be included. In order to prevent duplications, in case the patient followed her treatment and follow-up at another site, she will be enrolled as per the site where the diagnosis was made, requesting information of the treatment and progression, when possible.\\n6. Availability of clinical, epidemiological and progress data.\\n\\nExclusion Criteria:\\n\\nPatients who do not wish to participate in the study for any reason could not be included in the study.</td>\n","    </tr>\n","    <tr>\n","      <th>35</th>\n","      <td>The trial with NCT ID number NCT04074720 has the following eligbility criteria, for inclusion and exclusion Inclusion Criteria:\\n\\n* Adults \\&gt;18 years old at time of consent\\n* Subject must be capable to giving informed consent or have an acceptable surrogate capable of giving consent on the subject behalf.\\n* Patients with carcinoma in situ or invasive breast cancer\\n* Patient must be undergoing one of the following:\\n\\n  * definitive surgical tumor resection for breast cancer OR\\n  * placement of a vascular access device as a prelude to neoadjuvant therapy for breast cancer OR\\n  * neurosurgical resection of a brain metastasis from primary breast cancer.\\n\\nExclusion Criteria:\\n\\n* \\&lt;18 years old\\n* Not able to give informed consent and does not have acceptable surrogate capable to giving informed consent.\\n* Active drug/alcohol dependence or abuse history</td>\n","    </tr>\n","    <tr>\n","      <th>38</th>\n","      <td>The trial with NCT ID number NCT06087120 has the following eligbility criteria, for inclusion and exclusion Inclusion Criteria:\\n\\n* Female,18 years old and older,\\n* Are diagnosed with stage II-III HER2+/Triple Negative breast cancer and indicated for neoadjuvant chemotherapy,\\n* FFPE sample is available at the time of diagnosis and operation,\\n* Are voluntary to participate in the study.\\n\\nExclusion Criteria:\\n\\n* Recurrent breast cancer,\\n* Other cancer metastasis to the breast,\\n* Have been or are being treated for cancer,\\n* Patients did not agree to participate in the studies.</td>\n","    </tr>\n","    <tr>\n","      <th>39</th>\n","      <td>The trial with NCT ID number NCT01785420 has the following eligbility criteria, for inclusion and exclusion Inclusion Criteria:a.\\n\\n1. Female subjects aged 18 years or older.\\n2. Histologically and/or cytologically confirmed diagnosis of breast cancer. Clinical stages breast cancer: HER2 positive, T1 or T2 or T3, N0 or N1, resectable T4, or resectable N2, (all M0)\\n3. Documentation of erbB-2 gene amplification by FISH (as defined by a ratio \\&gt;2.2) or chromogenic in situ hybridization (CISH, as defined by the manufacturer's kit instruction) or documentation of erbB-2-overexpression by IHC (defined as IHC3+, or IHC2+ with FISH or CISH confirmation) based on local laboratory.\\n4. LVEF within institutional range of normal as measured by MUGA or ECHO.\\n5. Screening laboratory values within the following parameters:\\n\\n   1. Absolute neutrophil count (ANC) ≥1.5 x 109 /L (1500/mm3)\\n   2. Platelet count ≥100 x 109/L (100,000/mm3)\\n   3. Hemoglobin ≥9.0 g/dL (90 g/L)\\n   4. Serum creatinine ≤1.5 x upper limit of normal (ULN)\\n   5. Total bilirubin ≤1.5 x ULN (\\&lt;3 ULN if Gilbert's disease) 6Aspartate aminotransferase (AST) and/or alanine aminotransferase (ALT)\\n\\n      * 2.5 x ULN\\n\\nExclusion Criteria:\\n\\n1. Bilateral breast cancer\\n2. Active uncontrolled cardiac disease, including cardiomyopathy, CHF (New York Heart Association \\[NYHA\\] functional classification of ≥3), unstable angina, and myocardial infarction (within 12 months of study entry).\\n3. Inadequately controlled hypertension (ie, systolic blood pressure \\[BP\\] \\&gt; 180 mm Hg or diastolic BP \\&gt; 100 mm Hg).\\n4. Family history of congenital long or short QT syndrome, Brugada syndrome or QT/QTc interval \\&gt; 0.45 second or known history of QT/QTc prolongation or torsade de pointe (TdP).\\n5. Significant chronic gastrointestinal disorder with diarrhea as a major symptom (eg, Crohn's disease, malabsorption, or grade ≥2 diarrhea of any etiology at baseline).\\n6. Women who are pregnant, breast-feeding.</td>\n","    </tr>\n","  </tbody>\n","</table><br><label><b>dtype:</b> object</label>"]},"metadata":{},"execution_count":65}]},{"cell_type":"code","source":["import openai\n","import tiktoken\n","from scipy import spatial\n","import pandas as pd\n","import ast\n","import openai\n","\n","# Function to get text embeddings\n","def text_embedding(text):\n","    response = client.embeddings.create(model=\"text-embedding-ada-002\", input=text)\n","    return response.data[0].embedding\n","\n","# Apply the text_embedding function to the 'text' column\n","clinical_trials_data['embedding'] = clinical_trials_data['text'].apply(lambda x: text_embedding(x))\n","\n","clinical_trials_data = clinical_trials_data.assign(embedding = (clinical_trials_data[\"text\"].apply(lambda x : text_embedding(x))))\n","print(clinical_trials_data.head())"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"q3pLV_YIxLkg","executionInfo":{"status":"ok","timestamp":1722378475827,"user_tz":420,"elapsed":565660,"user":{"displayName":"Nainika Reddy","userId":"15989986900907940721"}},"outputId":"afae8a40-6c4d-4183-c9ce-047c2abf6308"},"execution_count":66,"outputs":[{"output_type":"stream","name":"stdout","text":["         NCT ID   Acronym Overall Status  Start Date  \\\n","14  NCT06155331   Unknown     RECRUITING     2023-12   \n","34  NCT04603820  EMBARCAM     RECRUITING  2019-11-18   \n","35  NCT04074720   Unknown     RECRUITING  2018-05-10   \n","38  NCT06087120   Unknown     RECRUITING  2023-09-16   \n","39  NCT01785420   Unknown     RECRUITING     2013-05   \n","\n","                                           Conditions  \\\n","14                        Breast Cancer Stage 2 and 3   \n","34                        Breast Cancer and Pregnancy   \n","35  Breast Cancer, Invasive Breast Cancer, Carcino...   \n","38  Breast Cancer Female, Stage II Breast Cancer, ...   \n","39  Carcinoma Breast Stage I, HER2 Positive Breast...   \n","\n","                                        Interventions  \\\n","14  Fenofibrate, Placebo, Doxorubicin, Cyclophosph...   \n","34                            No interventions listed   \n","35  Tissue Sample collection, Blood Sample Collect...   \n","38                            No interventions listed   \n","39                               Trastuzumab, Placebo   \n","\n","                                            Locations Primary Completion Date  \\\n","14                                      Tanta - Egypt                 2024-12   \n","34  Oviedo - Spain, Badalona - Spain, Terrassa - S...                 2040-01   \n","35                       Philadelphia - United States              2028-08-11   \n","38  Ho Chi Minh City - Vietnam, Ho Chi Minh City -...              2025-12-01   \n","39                                     Mumbai - India                 2025-04   \n","\n","   Study First Post Date Last Update Post Date      Study Type         Phases  \\\n","14            2023-12-04            2023-12-18  INTERVENTIONAL         PHASE4   \n","34            2020-10-27            2024-04-15   OBSERVATIONAL  Not Available   \n","35            2019-08-30            2023-08-15  INTERVENTIONAL             NA   \n","38            2023-10-17            2023-10-18   OBSERVATIONAL  Not Available   \n","39            2013-02-07            2023-11-22  INTERVENTIONAL         PHASE3   \n","\n","                                          Eligibility  \\\n","14  Inclusion Criteria:\\n\\n* Age ≥ 18 years old.\\n...   \n","34  Inclusion Criteria:\\n\\n1. The patient should h...   \n","35  Inclusion Criteria:\\n\\n* Adults \\>18 years old...   \n","38  Inclusion Criteria:\\n\\n* Female,18 years old a...   \n","39  Inclusion Criteria:a.\\n\\n1. Female subjects ag...   \n","\n","                                                 text  \\\n","14  The trial with NCT ID number NCT06155331 has t...   \n","34  The trial with NCT ID number NCT04603820 has t...   \n","35  The trial with NCT ID number NCT04074720 has t...   \n","38  The trial with NCT ID number NCT06087120 has t...   \n","39  The trial with NCT ID number NCT01785420 has t...   \n","\n","                                            embedding  \n","14  [-0.014353722333908081, -0.019298672676086426,...  \n","34  [-0.027597151696681976, -0.020099356770515442,...  \n","35  [-0.019633859395980835, -0.01601286046206951, ...  \n","38  [-0.02823072299361229, -0.006393544841557741, ...  \n","39  [-0.033659253269433975, -0.005904540419578552,...  \n"]}]},{"cell_type":"code","source":["def strings_ranked_by_relatedness(\n","    query: str,\n","    df: pd.DataFrame,\n","    relatedness_fn = lambda x, y: 1 - spatial.distance.cosine(x, y),\n","    top_n: int = 1000\n","):\n","\n","    EMBEDDING_MODEL = \"text-embedding-ada-002\"\n","    query_embedding_response = openai.embeddings.create(\n","        model = EMBEDDING_MODEL,\n","        input = query,\n","    )\n","    query_embedding = query_embedding_response.data[0].embedding\n","    strings_and_relatednesses = [\n","        (row[\"text\"], relatedness_fn(query_embedding, row[\"embedding\"]))\n","        for i, row in df.iterrows()\n","    ]\n","    strings_and_relatednesses.sort(key = lambda x: x[1], reverse = True)\n","    strings, relatednesses = zip(*strings_and_relatednesses)\n","    return strings[:top_n], relatednesses[:top_n]\n","\n","strings, relatednesses = strings_ranked_by_relatedness(\"Clinical Trials\", clinical_trials_data, top_n = 3)\n","for string, relatedness in zip(strings, relatednesses):\n","    print(f\"{relatedness = :.3f}\")\n","    display(string)\n","\n","def num_tokens(text: str) -> int:\n","    encoding = tiktoken.encoding_for_model(\"gpt-4o\")\n","    return len(encoding.encode(text))\n","\n","def query_message(\n","    query: str,\n","    df: pd.DataFrame,\n","    model: str,\n","    token_budget: int\n",") :\n","    strings, relatednesses = strings_ranked_by_relatedness(query, df)\n","    introduction = 'Use the below content to match patients to clinical trials. Explain why the patient does not match any of the eligibility criteria.\"'\n","    question = f\"\\n\\nQuestion: {query}\"\n","    message = introduction\n","    for string in strings:\n","        next_row = f'\\n\\nClinical trial section:\\n\"\"\"\\n{string}\\n\"\"\"'\n","        if (\n","            num_tokens(message + next_row + question)\n","            > token_budget\n","        ):\n","            break\n","        else:\n","            message += next_row\n","    return message + question\n","\n","def ask(\n","    query: str,\n","    df: pd.DataFrame = clinical_trials_data,\n","    model: str = \"gpt-4o\",\n","    token_budget: int = 25000,\n","    print_message: bool = False,\n",") :\n","    message = query_message(query, df, model=model, token_budget = token_budget)\n","    if print_message:\n","        print(message)\n","    messages = [\n","        {\"role\": \"system\", \"content\": \"You match patients to clinical trials that they are eligible for.\"},\n","        {\"role\": \"user\", \"content\": message},\n","    ]\n","    response = openai.chat.completions.create(\n","        model = model,\n","        messages = messages,\n","        temperature = 0\n","    )\n","    #response_message = response[\"choices\"][0][\"message\"][\"content\"]\n","    response_message = response.choices[0].message.content\n","    return response_message"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":394},"id":"PvzMm_PDkG5f","executionInfo":{"status":"ok","timestamp":1722382655847,"user_tz":420,"elapsed":875,"user":{"displayName":"Nainika Reddy","userId":"15989986900907940721"}},"outputId":"3c50526d-866d-4746-b8d1-2e90dc049603"},"execution_count":82,"outputs":[{"output_type":"stream","name":"stdout","text":["relatedness = 0.817\n"]},{"output_type":"display_data","data":{"text/plain":["'The trial with NCT ID number NCT05044689 has the following eligbility criteria, for inclusion and exclusion Case Group - Patients must have histologically confirmed diagnosis of colorectal or breast cancer.\\n\\nControl Group - Patients must not have a diagnosis of cancer.'"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{}},{"output_type":"stream","name":"stdout","text":["relatedness = 0.816\n"]},{"output_type":"display_data","data":{"text/plain":["'The trial with NCT ID number NCT05406531 has the following eligbility criteria, for inclusion and exclusion Inclusion Criteria:\\n\\n* Women over the age of 18\\n* Breast cancer patients at the end of adjuvant treatment\\n\\nExclusion Criteria:\\n\\n* Patients without a mobil device (\"smart\" mobile phone)\\n* Patients without internet access\\n* Patients with diagnosed: psychotic disorder; severe depressive episode; panic disorder; bipolar disorder; personality disorder associated with uncontrollable mood swings; PTSD; suicidal attempts and active suicidal ideation; disability pension due to non-specific mental or somatic problems; hospitalization due to a psychiatric disorder in the past year'"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{}},{"output_type":"stream","name":"stdout","text":["relatedness = 0.816\n"]},{"output_type":"display_data","data":{"text/plain":["'The trial with NCT ID number NCT05704842 has the following eligbility criteria, for inclusion and exclusion Inclusion Criteria:\\n\\n* Women with curative-intent breast cancer who plan to undergo at least 4 cycles of chemotherapy.\\n* Age \\\\> 18 years\\n* ECOG performance score \\\\< 3\\n* English-speaking\\n* with sufficient vision/hearing or family support\\n* Coronary artery disease, if cleared by cardiologist\\n* Subject must have smart phone, computer or tablet.\\n* Willingness to be randomized\\n\\nExclusion Criteria:\\n\\n* Medical or psychiatric conditions (beyond those related to breast cancer and its treatment) that would impair our ability to test study hypotheses (psychotic disorders, dementia, inability to give informed consent or follow instructions).\\n* Patients with overt evidence of a psychiatric disorder.\\n* Coronary artery disease, not cleared by cardiologist.\\n* Contraindication to exercise.\\n* Chronic fatigue syndrome.'"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{}}]},{"cell_type":"code","source":["query = f\"\"\"You are a doctor seeing a patient diagnosed with a type of breast cancer with the following medical history. {patient_summary}. Use this information and the clinical trial inclusion/exclusion criteria to identify up to 4 clinical trials that the patient is eligible for. The patient must meet all of the criteria listed for the clinical trial. Identify and report the NCT ID number and the clinical trial eligibility (inclusion and exclusion) criteria. For each eligibility criterion for the trial, explain why the patient is eligible. If the patient does not match the criteria for any of the trials, explain why.\"\"\""],"metadata":{"id":"FWQCbaIQxcaE","executionInfo":{"status":"ok","timestamp":1722382659974,"user_tz":420,"elapsed":186,"user":{"displayName":"Nainika Reddy","userId":"15989986900907940721"}}},"execution_count":83,"outputs":[]},{"cell_type":"code","source":["resp_0 = ask(query)"],"metadata":{"id":"9-8S-tHeXGXF","executionInfo":{"status":"ok","timestamp":1722382685372,"user_tz":420,"elapsed":24764,"user":{"displayName":"Nainika Reddy","userId":"15989986900907940721"}}},"execution_count":84,"outputs":[]},{"cell_type":"code","source":["print(resp_0)"],"metadata":{"id":"tNvRDGMUyM1d","executionInfo":{"status":"ok","timestamp":1722382685374,"user_tz":420,"elapsed":12,"user":{"displayName":"Nainika Reddy","userId":"15989986900907940721"}},"colab":{"base_uri":"https://localhost:8080/"},"outputId":"801e1c76-483f-4a6b-df0a-395991ddb318"},"execution_count":85,"outputs":[{"output_type":"stream","name":"stdout","text":["Based on the provided patient summary and the clinical trial eligibility criteria, Mrs. Paulita78 Watsica258 does not match the criteria for any of the clinical trials listed. Here is a detailed explanation of why she does not match the criteria for each trial:\n","\n","1. **NCT04360330**\n","   - **Inclusion Criteria:**\n","     - Female, ≥ 50 years of age. (Eligible)\n","     - Oncotype or MammaPrint diagnosis results are required prior to the start of treatment. (Not mentioned)\n","     - Histologically confirmed invasive breast cancer. (Eligible)\n","     - Clinical stage T1N0M0. (Eligible)\n","     - Receptor status: ER/PR positive and HER2 negative. (Not mentioned)\n","     - Unifocal breast cancer. (Not mentioned)\n","     - ECOG 0, 1. (Not mentioned)\n","     - Ability to undergo MRI. (Not mentioned)\n","     - WOCBP must agree to use adequate contraception or agree to undergo sexual abstinence. (Not applicable)\n","     - Ability to understand the investigational nature, potential risks and benefits of the research study and willingness to sign the written informed consent and HIPAA document(s). (Eligible)\n","   - **Exclusion Criteria:**\n","     - Patients without histologically confirmed invasive breast cancer. (Eligible)\n","     - Patients without Oncotype or MammaPrint diagnosis results at the start of treatment. (Not mentioned)\n","     - Patients with metastatic disease. (Eligible)\n","     - ECOG 2, 3, 4. (Not mentioned)\n","     - Patients that are unable to undergo MRI. (Not mentioned)\n","     - Prior history of radiation to the chest. (Eligible)\n","     - History of collagenous disease. (Eligible)\n","     - Any serious medical or psychiatric illness/condition likely to interfere or limit compliance with study requirements/treatment. (Eligible)\n","     - Diagnosis of another primary malignancy within the last 5 years. (Eligible)\n","     - Patients unable to consent, who are pregnant or nursing, or are prisoners. (Eligible)\n","\n","   **Reason for Ineligibility:** The patient’s receptor status (ER/PR and HER2) and Oncotype or MammaPrint diagnosis results are not provided, which are required for inclusion.\n","\n","2. **NCT05033925**\n","   - **Inclusion Criteria:**\n","     - Female, at least 18 years old. (Eligible)\n","     - Welfare scale 0, 1, and 2 (ECOG - WHO). (Not mentioned)\n","     - Patients with stage IV breast cancer. (Not eligible, patient has Stage 1A)\n","     - Patients who are willing to participate in the test and sign an informed consent. (Eligible)\n","     - Patients who undergo breast cancer chemotherapy with luminal B sub-type or triple negative with anthracycline base. (Not mentioned)\n","     - Patients who are willing and able to fill out a questionnaire. (Eligible)\n","     - The patients who are willing and able to comply with the test protocols during the test. (Eligible)\n","   - **Exclusion Criteria:**\n","     - Unable to meet the test protocol. (Eligible)\n","     - Patients with liver and kidney disorders. (Eligible)\n","     - Patients with other diseases/disorders that are meaningful according to the investigators will be excluded from the test. (Eligible)\n","     - Patients with cancer that has metastasized to the brain. (Eligible)\n","     - Pregnant women and breastfeeding mothers. (Eligible)\n","     - Patients with the ejection fraction smaller-than or equal to 55%. (Not mentioned)\n","\n","   **Reason for Ineligibility:** The patient has Stage 1A breast cancer, not Stage IV.\n","\n","3. **NCT04965909**\n","   - **Inclusion Criteria:**\n","     - Woman aged between 18 - 65 years. (Eligible)\n","     - Diagnosis of stage 0 - III breast cancer. (Eligible)\n","     - Primary treatment (surgery, radiotherapy and chemotherapy) completed at least 3 months ago may still be receiving hormonal therapy. (Eligible)\n","     - Pain related to primary treatment in the last 6 months. (Not mentioned)\n","     - Access to Internet and an electronic device that allows the use of the applications used in this study and skills for their use or assistance from a close person who has them. (Eligible)\n","     - Ability to communicate fluently verbally and in writing in the language of the research team (Spanish). (Not eligible, primary language is English)\n","     - Approval of participation in the study by the coordinator of the health team that assisted her during the course of cancer and its treatment. (Not mentioned)\n","   - **Exclusion Criteria:**\n","     - Another previous type of cancer or breast cancer recurrence in a period of less than 1 year. (Eligible)\n","     - Medical diagnosis of a neurological, autoimmune or cardiovascular disease. (Eligible)\n","     - Some type of pathology that is associated with a contraindication to physical exercise. (Eligible)\n","     - Diagnosis of serious psychiatric or neurologic disorders that do not allow the participant to follow orders. (Eligible)\n","\n","   **Reason for Ineligibility:** The patient’s primary language is English, not Spanish.\n","\n","4. **NCT05483439**\n","   - **Inclusion Criteria:**\n","     - Female patients aged ≥ 18 but ≤ 75 years. (Eligible)\n","     - Diagnosis of breast cancer meets the following criteria: Stage II-III patients who meet the 8th edition of AJCC Cancer Staging Manual and meet the indications of neoadjuvant therapy. (Not eligible, patient has Stage 1A)\n","     - Diagnosis of breast cancer meets the following criteria: Histologically confirmed invasive breast cancer. (Eligible)\n","     - KPS score≥70. (Not mentioned)\n","     - The functional level of major organs must conform to the following requirements. (Not mentioned)\n","     - Patients who participate in the trial voluntarily, sign an informed consent, have good compliance and are willing to comply with the follow-up visit. (Eligible)\n","   - **Exclusion Criteria:**\n","     - Previously received any anti-tumor therapy (chemotherapy, radiotherapy, molecular targeted therapy, endocrine therapy, etc.). (Not eligible, patient has received radiation therapy)\n","     - Patients who are concurrently receiving other anti-tumor therapy. (Eligible)\n","     - Bilateral breast cancer, inflammatory breast cancer, or occult breast cancer. (Eligible)\n","     - Stage IV breast cancer. (Eligible)\n","     - Intolerant to herbs or poor compliance. (Eligible)\n","     - With a history of any malignancies other than breast cancer in the past 5 years. (Eligible)\n","     - Severe heart, liver, kidney and other important organ dysfunction. (Eligible)\n","     - Inability to swallow, chronic diarrhea and intestinal obstruction, and having many factors that affect drug administration and absorption. (Eligible)\n","     - Participated in clinical trials of other drugs within 4 weeks before enrollment. (Eligible)\n","     - Known history of allergy to the drug components of this regimen. (Eligible)\n","     - History of immunodeficiency, including HIV positive, HCV, live active hepatitis B or other acquired or congenital immune deficiency diseases, or a history of organ transplantation. (Eligible)\n","     - Have used drugs that affect immune function within 1 year. (Eligible)\n","     - Once suffered from any heart disease. (Eligible)\n","     - Pregnant, lactating women, fertile women with positive baseline pregnancy test or in the entire women of reproductive age who were unwilling to use effective contraception during the trial. (Eligible)\n","     - According to the investigator's judgment, there are comorbidities that seriously endanger the patient's safety or affect the patient's ability to complete the study. (Eligible)\n","     - A clear past history of neurological or psychiatric disorders, including epilepsy or dementia. (Eligible)\n","\n","   **Reason for Ineligibility:** The patient has Stage 1A breast cancer, not Stage II-III.\n","\n","Given the detailed analysis, Mrs. Watsica does not meet the eligibility criteria for any of the clinical trials listed. The primary reasons include the stage of her breast cancer, missing specific diagnostic results, and language requirements.\n"]}]}]}