This repo contains our code for the paper Large Language Models for Integrating Social Determinant of Health Data: A Case Study on Heart Failure 30-Day Readmission Prediction.

Heart failure 30-day hospital readmission prediction (HF_readmission_prediction):

python 3.9
imblearn==0.0
joblib==1.2.0
numpy==1.24.4
pandas==2.0.0
pymongo==4.7.0
scikit_learn==1.4.2
shap==0.45.0
tqdm==4.65.0
xgboost==1.7.6

LLMs to annotate SDOH variables (LLM_SDOH_annotation):

python 3.9
datasets==2.11.0
huggingface_hub==0.17.3
numpy==1.24.4
pandas==2.0.0
peft==0.10.0
torch==2.0.0
tqdm==4.65.0
transformers==4.34.1

The social determinants of health (SDOH) datasets used in this study can be found below:

For zero-shot and 1-shot inference of SDOH Domains for AHRQ and NaNDA variables, please use the commands in LLM_SDOH_annotation/commands folder for experiments.

• Full list of SDOH variables used from AHRQ, NaNDA (Zenodo)
• Instructions for NaNDA Variable Annotation (Zenodo)