pyhealth

SUMMARY

What it does

This skill provides procedural guidance for building clinical/healthcare deep-learning pipelines with PyHealth. It covers loading EHR/signal/imaging datasets (MIMIC-III/IV, eICU, OMOP, SleepEDF, ChestXray14, EHRShot), defining prediction tasks (mortality, readmission, length-of-stay, drug recommendation, sleep staging, ICD coding, EEG events), instantiating models (Transformer, RETAIN, GAMENet, SafeDrug, MICRON, StageNet, AdaCare, CNN/RNN/MLP), training with the PyHealth Trainer, computing clinical metrics, and using medical code utilities (ICD/ATC/NDC/RxNorm lookup and cross-mapping). The skill emphasizes a 5-stage pipeline (Dataset → Task → Model → Trainer → Metrics) and includes critical implementation notes, such as passing SampleDataset to models, splitting by patient, and matching tasks to datasets. It also provides installation instructions using uv and references to detailed documentation.