Open Source, Enterprise and Modern Health Information System

Electronic Health Record Analysis with Python.

Code for "Graph Neural Network on Electronic Health Records for Predicting Alzheimer’s Disease"

Open-source SDK for healthcare AI: FHIR endpoints, EHR integration, and deployment tooling in Python 💫 🏥

[EMNLP'24] EHRAgent: Code Empowers Large Language Models for Complex Tabular Reasoning on Electronic Health Records

Patient2Vec: A Personalized Interpretable Deep Representation of the Longitudinal Electronic Health Record

🧪Yet Another ICU Benchmark: a holistic framework for the standardization of clinical prediction model experiments. Provide custom datasets, cohorts, prediction tasks, endpoints, preprocessing, and models. Paper: https://arxiv.org/abs/2306.05109

NER and Relation Extraction from Electronic Health Records (EHR).

FHIR MCP Server for handling medical data standard.

An open source implementation of the paper: "Sequential Diagnosis with Language Models" From Microsoft Built with Swarms Framework

FHIR Python Analysis Client and Kit (FHIRPACK) is a general purpose FHIR client that simplifies the access, analysis and representation of FHIR and EHR data using PANDAS, an ETL philosophy and a functional syntax. It was initially developed at the IKIM and HDDBS in Germany. Read more at https://zenodo.org/record/8006589

A Comprehensive Benchmark For COVID-19 Predictive Modeling Using Electronic Health Records

Fact Verification for Clinical Notes with LLMs

HealthFlow: A Self-Evolving AI Agent with Meta Planning for Autonomous Healthcare Research

[EMNLP'24] MedAdapter: Efficient Test-Time Adaptation of Large Language Models Towards Medical Reasoning

Code for the paper: Multi-Label Clinical Time-Series Generation via Conditional GAN (IEEE TKDE)

A Multimodal Transformer: Fusing Clinical Notes With Structured EHR Data for Interpretable In-Hospital Mortality Prediction

[Cell Patterns] COVID-19 EHR data analysis pipeline

[ML4H 2022] This is the code for our paper `Counterfactual and Factual Reasoning over Hypergraphs for Interpretable Clinical Predictions on EHR'.

[WWW-2025] ColaCare: Enhancing Electronic Health Record Modeling through Large Language Model-Driven Multi-Agent Collaboration