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).
npx skills add LeonChaoX/qinyan-academic-skills --skill pyhealth --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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 - **Implementing healthcare models**: RETAIN, SafeDrug, GAMENet, StageNet, Transformer for EHR - **Evaluating clinical models**: Fairness metrics, calibration, interpretability, uncertainty quantification ## Core Capabilities PyHealth operates through a modular 5-stage pipeline optimized for healthcare AI: 1. **Data Loading**: Access 10+ healthcare datasets with standardized i
- Overview
- When to Use This Skill
- Core Capabilities
- Quick Start Workflow
- Detailed Documentation
- 1. Datasets and Data Structures
- 2. Medical Coding Translation
- 3. Clinical Prediction Tasks
- 4. Models and Architectures
- 5. Data Preprocessing
- 6. Training and Evaluation
- Installation
- Common Use Cases
- Use Case 1: ICU Mortality Prediction
uv pip install pyhealth
What does the pyhealth skill do?
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).
How do I install it?
Run `npx skills add LeonChaoX/qinyan-academic-skills --skill pyhealth --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From LeonChaoX/qinyan-academic-skills, a repository with 759 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.