pyhealth - Healthcare AI toolkit for clinical machine learning
Develop, train, evaluate, and deploy healthcare machine learning models using clinical data, medical codes, physiological signals, and healthcare datasets.
Tags
Updated: 2026-10-03Capabilities
Typical Inputs
Typical Outputs
What this skill does
- Load healthcare datasets
- Define clinical prediction tasks
- Translate medical coding systems
- Process clinical data
- Select healthcare models
- Preprocess physiological signals
- Train machine learning models
- Evaluate clinical models
- Calibrate model predictions
- Interpret model predictions
Inputs
- Healthcare datasets
- Clinical prediction tasks
- Medical coding systems
- Clinical text
- Physiological signals
- Medical images
- Model configurations
- Training parameters
Outputs
- Trained machine learning models
- Evaluation results
- Clinical metrics
- Calibrated predictions
- Interpretability outputs
- Uncertainty estimates
Requirements
- Python 3.7 or later
- PyTorch 1.8 or later
- NumPy
- pandas
- scikit-learn