PyHealth

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 interfaces
2. Task Definition: Apply 20+ predefined clinical prediction tasks or create custom tasks
3. Model Selection: Choose from 33+ models (baselines, deep learning, healthcare-specific)
4. Training: Train with automatic checkpointing, monitoring, and evaluation
5. Deployment: Calibrate, interpret, and validate for clinical use

Performance: 3x faster than pandas for healthcare data processing

Quick Start Workflow

from pyhealth.datasets import MIMIC4Dataset
from pyhealth.tasks import mortality_prediction_mimic4_fn
from pyhealth.datasets import split_by_patient, get_dataloader
from pyhealth.models import Transformer
from pyhealth.trainer import Trainer