pyhealth
Category: clinical-and-health · License: MIT · Version: 1.1
Tags: clinical machine learning, EHR, MIMIC, healthcare AI, deep learning
When to use it
Builds clinical deep-learning pipelines with PyHealth using its Dataset → Task → Model → Trainer → Metrics pattern. Covers loading MIMIC-III/IV, eICU, OMOP, SleepEDF, ChestXray14 and EHRShot data, defining prediction tasks (mortality, readmission, length of stay, drug recommendation, sleep staging, ICD coding, EEG events), models such as Transformer, RETAIN, GAMENet, SafeDrug and StageNet, training with Trainer, and ICD/ATC/NDC/RxNorm code lookup and cross-mapping. Use when building a clinical prediction model on EHR data. Use when working with MIMIC or eICU datasets. Use when recommending drugs or staging sleep from signals. Use when mapping medical codes between ICD, ATC, NDC or RxNorm. Not for generic PyTorch on tabular data.Example requests
Ask your agent in plain language, for example:- “I have MIMIC-IV downloaded locally. How do I train a model to predict in-hospital mortality and evaluate it properly?”
- “My script crashes at
MortalityPredictionMIMIC3(...)when I run it onMIMIC4Dataset(root='/data/mimiciv/2.2', tables=['diagnoses_icd','procedures_icd']). Then I pass the dataset directly toTransformer(dataset=base, feature_keys=['conditions','procedures'], label_key='label', mode='binary')and get an error. Parsing also takes 40 minutes every time I rerun it. What’s wrong?” - “I’ve got nightly polysomnography recordings from a sleep clinic as EDF files with technician-scored hypnograms. I want a neural network that labels each 30-second epoch as wake, REM or N1-N3, and I’d like to avoid hand-writing the training loop. What’s a good approach?”
Install
/plugin marketplace add KalarisLabs/research-agent-skills and install the whole clinical-and-health category with /plugin install clinical-and-health@research-agent-skills.