MEDIQA-Chat-2023

• Website: https://sites.google.com/view/mediqa2023/clinicalnlp-mediqa-chat-2023
• Google group: https://groups.google.com/g/mediqa-nlp

Tasks

• Task A - Short Dialogue2Note Summarization: generating a section summary (section header and content) associated with the short input conversation. Section header will be one of twenty normalized section labels provided with the training data.
• Task B - Full Dialogue2Note Summarization: generating a clinical note from the full input conversation. The note should include all relevant sections. Accepted first-level section headers are: "HISTORY OF PRESENT ILLNESS", "PHYSICAL EXAM", "RESULTS", "ASSESSMENT AND PLAN".
• Task C - Note2Dialogue Generation: generating a doctor-patient conversation from the full input note. This task addresses data augmentation through the generation of synthetic conversations from clinical notes. We encourage the participants to apply the models developed for this task to generate additional data for tasks A & B.

For all tasks, we encourage participants to try different and original approaches to contribute to the community with new research insights. All participating teams will be invited to submit papers describing their models and methods to the ClinicalNLP workshop at ACL 2023.

Datasets

Training & Validation Sets: Released to the registered participants on February 10, 2023. Test Sets: Released to the participants on March 15, 2023.

(Post-challenge) The MEDIQA-Chat shared tasks used the MTS-Dialog dataset for Task A and the ACI-Bench dataset for Task B and Task C. Fore more information about the datasets:

• MTS-Dialog Dataset: https://github.com/abachaa/MTS-Dialog
• ACI-Bench Dataset: https://github.com/wyim/aci-bench

Submission Instructions

• Each team is allowed to submit a maximum of 3 runs for each task.

• Each team is required to submit the code/models used to generate the outputs.

• Each run file should be named as follows: task{A|B|C}_teamName_run{1|2|3}.csv

• Task A Format: The run file should be a csv file with 3 columns: "TestID", "SystemOutput1", and "SystemOutput2".

  • SystemOutput1 is the generated note section header.
  • SystemOutput2 is the generated note section content (summary of the conversation).

• Format for tasks B & C: The run file should be a csv file with 2 columns: "TestID" and "SystemOutput".

  • For task B: SystemOutput is the full clinical note including the four main sections.
  • For task C: SystemOutput is the full conversation associated with the input note. The doctor and patient turns should start with "Doctor:" and "Patient:" (without quotes).

• Please use the submission_checker.py script to check and validate your run file before submission.

• The submission forms will be made available with the release of the test sets on March 15, 2023.

• We will provide more guidelines on preparing and submitting the codes/models for confirmation of the results.

• After the competition, we encourage the teams to release their codes publicly with the publication of their papers.

Evaluation Methods

• For the three tasks, we will use ensemble metrics that correlate well with human judgments.
• These ensemble metrics combine SOTA evaluation metrics including ROUGE, BERTScore and BLEURT.

Scripts

• Script for submission format checking => scripts/submission_checker.py

• Script for task A/B evaluation => scripts/evaluate_summarization.py

• Script for creating the virtual environment for using the evaluation script => scripts/install_evalvenv.sh

• Script for task B/C source/tgt data creation => scripts/divide_and_output_files.py

Submission & Evaluation Process

• The training, validation and test sets will be released according to the schedule below.
• Participants will have access to the submission forms on March 15 to submit their runs and codes.
• Organisers will evaluate the submissions and release the results to the participants on March 31.
• Results will be considered official after submitting a working notes paper describing the used methods to the ACL-ClinicalNLP 2023 workshop.

Code Submission Guidelines

Please make sure that your inference code:

(1) can run within 48 hours for a size comparable to the train set, (2) takes less than the resources needed for a Standard_NC24 machines from azure ( https://learn.microsoft.com/en-us/azure/virtual-machines/nc-series ), (3) can run in a linux environment.

Your code package should at least include the following three files:

install.sh

• create an environment {teamname}_task{A,B,C}_venv
• activate your environment
• install all your requirements
• then close your environment

activate.sh

• activate your environment

decode_task{A,B,C}_run{1,2,3}.sh

• first argument should be the source text
• it is expected that the order of the resulting output be the same as the source text

In summary, for us to run we should be able to get quick-started by doing the following commands:

./install.sh
./activate.sh
decode_task{A,B,C}_run{1,2,3}.sh [input-csv-file]

• The input should be in the *.csv format of the original test files
• The output files should have the same format as the runs and should be named task{A|B|C}_teamName_run{1|2|3}.csv

• Our copy of the codes and models will be deleted after the release of the official results and confirmation emails will be sent to the participants.

Schedule

• All deadlines are 11:59PM UTC-12:00 (anywhere on Earth)
• Release of the training and validation sets: February 10, 2023
• Registration ends: March 3rd, 2023
• Release of the test sets: March 15, 2023
• Run & code submission deadline: March 22, 2023
• Release of the official results by the organizers: April 7, 2023
• Paper submission deadline: May 4, 2023
• Notification of acceptance: May 29, 2023
• Camera-ready paper due: June 6, 2023
• Pre-recorded video due: June 12, 2023
• ACL-ClinicalNLP Workshop: July 14, 2023, Toronto, Canada

Organizers:

• Asma Ben Abacha, Microsoft, USA
• Wen-wai Yim, Microsoft, USA
• Griffin Adams, Columbia University, USA
• Neal Snider, Microsoft/Nuance, USA
• Meliha Yetisgen, University of Washington, USA