Individual skill
pyhealth
Comprehensive healthcare AI toolkit for developing, testing, and deploying machine learning models with clinical data. This skill should be used when working with electronic health records (EHR), clinical prediction tasks (mortality, readmission, drug recommendation), medical coding systems (ICD, NDC, ATC), physiological signals (EEG, ECG), healthcare datasets (MIMIC-III/IV, eICU, OMOP), or implementing deep learning models for healthcare applications (RETAIN, SafeDrug, Transformer, GNN).
backend/cli/skills/biology/pyhealth/SKILL.md
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- Last checked
- Nov 2, 2026
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- Nov 6, 2026
- License
- Apache-2.0
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SKILL.mdcore · 17,934 bytesSKILL.mdcore · 17,934 bytesSKILL.mdcore · 17,934 bytesSKILL.mdcore · 17,934 bytesSKILL.mdcore · 17,934 bytesSKILL.mdcore · 17,934 bytesreferences/datasets.mddoc · 5,468 bytesreferences/medical_coding.mddoc · 8,476 bytesreferences/models.mddoc · 13,776 bytesreferences/preprocessing.mddoc · 14,388 bytesreferences/tasks.mddoc · 11,404 bytesreferences/training_evaluation.mddoc · 16,982 bytes
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# PyHealth: Healthcare AI Toolkit
## Overview
PyHealth is a comprehensive Python library for healthcare AI that provides specialized tools, models, and datasets for clinical machine learning. Use this skill when developing healthcare prediction models, processing clinical data, working with medical coding systems, or deploying AI solutions in healthcare settings.
## When to Use This Skill
Invoke this skill when:
- **Working with healthcare datasets**: MIMIC-III, MIMIC-IV, eICU, OMOP, sleep EEG data, medical images
- **Clinical prediction tasks**: Mortality prediction, hospital readmission, length of stay, drug recommendation
- **Medical coding**: Translating between ICD-9/10, NDC, RxNorm, ATC coding systems
- **Processing clinical data**: Sequential events, physiological signals, clinical text, medical images