pyhealth

Topics in the source

• PyHealth: Healthcare AI Toolkit
• Overview
• When to Use This Skill
• Core Capabilities
• Quick Start Workflow
• Detailed Documentation
• 1. Datasets and Data Structures
• 2. Medical Coding Translation

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. 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 PyHealth operates through a modular 5-stage pipeline optimized for healthcare AI: 1. Data Loading: Access 10+ healthcare datasets with standardized interfaces 2. Task Definition: Apply 20+ predefined clinical prediction tasks or create custom tasks 3. Model Selection: Choose from 3

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