PyHealth 2.0: A Comprehensive Open-Source Toolkit for Accessible and Reproducible Clinical Deep Learning

TL;DR

PyHealth 2.0 is an open-source toolkit that simplifies and accelerates clinical deep learning research by unifying datasets, models, and methods in a user-friendly, resource-efficient framework.

Contribution

It introduces a comprehensive, compatible, and accessible toolkit supporting diverse clinical data modalities and fostering an active community for reproducible healthcare AI research.

Findings

Supports 15+ datasets and 20+ clinical tasks within a single framework.

Achieves up to 39x faster processing and 20x lower memory usage.

Enables predictive modeling in as few as 7 lines of code.

Abstract

Difficulty replicating baselines, high computational costs, and required domain expertise create persistent barriers to clinical AI research. To address these challenges, we introduce PyHealth 2.0, an enhanced clinical deep learning toolkit that enables predictive modeling in as few as 7 lines of code. PyHealth 2.0 offers three key contributions: (1) a comprehensive toolkit addressing reproducibility and compatibility challenges by unifying 15+ datasets, 20+ clinical tasks, 25+ models, 5+ interpretability methods, and uncertainty quantification including conformal prediction within a single framework that supports diverse clinical data modalities - signals, imaging, and electronic health records - with translation of 5+ medical coding standards; (2) accessibility-focused design accommodating multimodal data and diverse computational resources with up to 39x faster processing and 20x lower memory usage, enabling work from 16GB laptops to production systems; and (3) an active open-source community of 400+ members lowering domain expertise barriers through extensive documentation, reproducible research contributions, and collaborations with academic health systems and industry partners, including multi-language support via RHealth. PyHealth 2.0 establishes an open-source foundation and community advancing accessible, reproducible healthcare AI. Available at pip install pyhealth.