PyHealth Clinical Pipelines
Skill Verifiziert AktivBuild clinical/healthcare deep-learning pipelines with PyHealth — loading EHR/signal/imaging datasets (MIMIC-III/IV, eICU, OMOP, SleepEDF, ChestXray14, EHRShot), defining tasks (mortality, readmission, length-of-stay, drug recommendation, sleep staging, ICD coding, EEG events), instantiating models (Transformer, RETAIN, GAMENet, SafeDrug, MICRON, StageNet, AdaCare, CNN/RNN/MLP), training with the PyHealth Trainer, computing clinical metrics, and using medical code utilities (ICD/ATC/NDC/RxNorm lookup and cross-mapping). Use this skill whenever the user mentions PyHealth, MIMIC, eICU, OMOP, EHR modeling, clinical prediction, drug recommendation, sleep staging, medical code mapping, ICD/ATC codes, or any healthcare ML pipeline that fits the dataset → task → model → trainer → metrics pattern, even if "PyHealth" isn't named explicitly.
To empower users to construct sophisticated clinical deep-learning pipelines efficiently by leveraging the PyHealth toolkit, from data loading to model training and evaluation.
Funktionen
- Loading diverse EHR/signal/imaging datasets (MIMIC, eICU, OMOP)
- Defining and executing clinical prediction tasks
- Instantiating various deep learning models
- Training models with PyHealth Trainer
- Using medical code lookup and cross-mapping utilities
Anwendungsfälle
- Building mortality prediction models on EHR data
- Developing drug recommendation systems
- Performing sleep staging on polysomnography signals
- Mapping and analyzing medical codes (ICD, ATC, RxNorm)
Nicht-Ziele
- Generic PyTorch modeling on tabular data without PyHealth structure
- Directly interfacing with raw medical imaging formats outside PyHealth's scope
- Providing a GUI for pipeline construction
Praktiken
- Clinical ML pipeline construction
- Data loading and preprocessing
- Model selection and training
- Medical code handling
Voraussetzungen
- Python >= 3.12
- uv package manager
- Agent supporting Agent Skills standard
Installation
npx skills add K-Dense-AI/claude-scientific-skillsFührt das Vercel skills CLI (skills.sh) via npx aus — benötigt Node.js lokal und mindestens einen installierten skills-kompatiblen Agent (Claude Code, Cursor, Codex, …). Setzt voraus, dass das Repo dem agentskills.io-Format folgt.
Qualitätspunktzahl
VerifiziertVertrauenssignale
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