pyhealth

Builds and validates PyHealth clinical machine-learning pipelines for EHR, signals, imaging, and medical codes. Use for PyHealth dataset loading, MIMIC-III/IV, eICU or OMOP prediction tasks, patient-level evaluation, mortality/readmission/length-of-stay modeling, medication recommendation, sleep staging, Trainer checkpoints, and ICD/ATC/NDC/RxNorm mapping.

Version

1.3

Compatibility

Requires Python 3.12 or 3.13 and PyHealth 2.0.2 (Torch 2.7.1). Network access is needed for installation, public datasets and uncached medical-code resources. Restricted clinical datasets require authorized local access.