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About pyhealth
pyhealth
Builds and validates PyHealth clinical machine-learning pipelines for EHR
pyhealth is an agent skill for building and validating clinical machine-learning pipelines with PyHealth, covering electronic health record sequences, physiological signals, imaging tasks and medical-code lookup. It also covers loading datasets such as MIMIC-III and MIMIC-IV. The pipeline runs Dataset, then Task, then Model, then Trainer, then Metrics. The skill targets PyHealth 2.0.2, verified against the released wheel, the current documentation and CPU runs on Python 3.12 with Torch 2.7.1. Its 1.x and 2.x interfaces differ, and the skill warns not to combine legacy Visit examples with the 2.x event and processor API. Before modelling, the skill asks you to establish the cohort, the prediction time, the observation window, the outcome horizon and the unit of evaluation. For general tabular learning that has no PyHealth dataset or task, the skill is optional. It includes a starter pipeline with a demo mode you can run to check the install. Use it for clinical prediction research with PyHealth. It is part of the k-dense-ai scientific agent skills repository on GitHub, which has about 49,600 stars. The listing shows it as free, and it has about 1,800 installs.
- Price
- Free
- Made by
- k-dense-ai
- Category
- AI Skills
- Website
- github.com/k-dense-ai/scientific-agent-skills/pyhealth