Update README.md

README.md

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 # T4
+
+# Introduction
 Code for paper "Estimating Trustworthy Treatment Effects for Antibiotic Stewardship in Sepsis"
+
+ In this paper, we propose a novel method to estimate Trustworthy Treatment effects for Time-to-Treatment antibiotic stewardship in sepsis (T4). 
+
+ <img src="src/Figure1_v3.png">
+
+We demonstrate that T4 can identify effective treatment timing with estimated trustworthy ITEs for antibiotic stewardship on two real-world datasets ([AmsterdamUMCdb](https://amsterdammedicaldatascience.nl/) and [MIMIC-III](https://mimic.physionet.org/)).
+
+# Requirement
+Ubuntu16.04, python 3.6
+
+Install [pytorch 1.4](https://pytorch.org/)
+
+# Datasets
+#### Studied variables
+The list of variables in MIMIC-III and AdmsterdamDB. There are 22 temporal covariates and 4 demographics andstatic variables. PT: Prothrombin Time; BUN: Blood Urea Nitrogen; WBC: White Blood Cells count.
+
+| Category 	|  	| MIMIC-III 	|  	| AmsterdamDB 	|  	|
+|---	|---	|---	|---	|---	|---	|
+|  	|  	| Mean 	| Std. 	| Mean 	| Std. 	|
+| Demographics 	| Age 	| 65.55 	| 16.44 	| 61.30 	| 17.90 	|
+|  	| Gender 	| 43\% Female 	| - 	| 42\% Female 	| - 	|
+|  	| Weight 	| 81.67 	| 25.50 	| 79.83 	| 13.61 	|
+|  	| Height 	| 169.30 	| 11.17 	| 175.15 	| 8.44 	|
+| Lab test 	| Anion gap 	| 13.35 	| 3.80 	| 8.70 	| 4.62 	|
+|  	| Bicarbonate 	| 25.65 	| 5.27 	| 25.63 	| 6.35 	|
+|  	| Bilirubin 	| 3.36 	| 6.41 	| 3.15 	| 6.85 	|
+|  	| Creatinine 	| 1.50 	| 1.46 	| 1.28 	| 1.03 	|
+|  	| Chloride 	| 104.00 	| 6.60 	| 108.60 	| 46.31 	|
+|  	| Glucose 	| 134.00 	| 66.83 	| 133.9 	| 45.74 	|
+|  	| Hematocrit 	| 29.96 	| 5.13 	| 38.98 	| 1.67 	|
+|  	| Hemoglobin 	| 10.09 	| 1.79 	| 12.57 	| 1.64 	|
+|  	| Lactate 	| 2.44 	| 2.14 	| 2.40 	| 2.95 	|
+|  	| Platelet 	| 235.05 	| 155.28 	| 220.82 	| 171.65 	|
+|  	| Potassium 	| 4.08 	| 0.63 	| 5.58 	| 602.56 	|
+|  	| PT 	| 17.76 	| 8.95 	| 1.59 	| 10.12 	|
+|  	| Sodium 	| 138.84 	| 5.32 	| 140.88 	| 43.45 	|
+|  	| BUN 	| 29.85 	| 23.54 	| 14.15 	| 9.80 	|
+|  	| WBC 	| 11.23 	| 7.64 	| 14.56 	| 11.80 	|
+| Vital signs 	| Heart Rate 	| 87.81 	| 18.30 	| 92.70 	| 23.65 	|
+|  	| SysBP 	| 120.92 	| 23.28 	| 126.05 	| 139.59 	|
+|  	| DiasBP 	| 61.41 	| 14.55 	| 60.77 	| 31.11 	|
+|  	| Meanbp 	| 78.70 	| 16.88 	| 82.12 	| 47.34 	|
+|  	| Respratory 	| 20.48 	| 5.90 	| 21.99 	| 7.71 	|
+|  	| Temperature 	| 36.96 	| 0.85 	| 36.73 	| 21.14 	|
+|  	| SpO2 	| 97.00 	| 3.27 	| 96.09 	| 7.43 	|
+
+#### Studied antibiotics
+The list of antibiotics in MIMIC-III Dataset. There are 18 kinds of antibiotics in total.
+| Category 	| Name 	|
+|---	|---	|
+| Antibiotic 	| Cefazolin, Cefepime, Ceftazidime, Ciprofloxacin, Clindamycin,  Erythromycin, Gentamicin, Levofloxacin, Metronidazole, Moxifloxacin, Piperacillin, Rifampin, Tobramycin, Vancomycin,  Amikacin, Ampicillin, Azithromycin, Aztreonam 	|
+
+
+# Train T4
+#### Running example 
+```
+bash run.sh 3 # number of follow-up steps
+```
+
+# Results
+Mortality rate comparison of two datasets. The results show that the mortality rate of patients who receive the antibiotics at the time werecommend is significantly lower than the patients who donot, indicating that our model offers effective timings of antibiotic administration that help to reduce the mortality rate.
+
+<img src="src/MIMIC-III_30d.png" width=40%><img src="src/MIMIC-III_60d.png" width=40%>
+<img src="src/AmsterdamUMCdb_30d.png" width=40%><img src="src/AmsterdamUMCdb_60d.png" width=40%>