sunlabuiuc/PyHealth

Health v2 · maintenance only

Adoption not part of the score

1673 stars · 823 forks observed · 2026-10-17

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

PyHealth is an open-source Python toolkit for clinical deep learning, unifying healthcare datasets (EHRs, physiological signals, medical imaging), prediction tasks, and ML models in a simple pipeline. It supports tasks like mortality prediction, readmission, and drug recommendation across 20+ clinical datasets with 50+ models.

Use cases

• train a mortality prediction model on MIMIC-III EHR data
• predict hospital readmission from electronic health records
• build drug recommendation models from clinical data
• process and preprocess EHR datasets for deep learning
• run clinical ML benchmarks on physiological signals and medical imaging
• prototype healthcare AI pipelines in under 15 lines of code

When to choose

• you need reproducible clinical deep learning pipelines on standard EHR datasets like MIMIC
• you want prebuilt clinical tasks and models instead of writing data loaders from scratch
• you work in healthcare ML research and need a unified dataset/task/model API

When to avoid

• you need production clinical deployment with regulatory compliance rather than research tooling
• your data is not healthcare-related
• you need a no-code or GUI tool rather than a Python library

Facets

library · maturity active

machine-learning deep-learning etl data-science healthcare machine-learning deep-learning data-science python ehr clinical-data mimic medical-imaging healthcare-ai clinical-deep-learning

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markdown · JSON · MCP: product_card(name="sunlabuiuc/PyHealth")