EHR Risk Framework vs ad-hoc clinical ML notebooks

Notebooks are excellent for exploration. A leakage-safe EHR risk prediction workbench helps when you need shared tasks, audits, calibration, and a reproducible train→explain→serve loop.

Need	Ad-hoc notebook	EHR Risk Framework
Index / horizon integrity	Easy to skip	Task YAML + leakage audit jobs
Calibration (Brier / ECE)	Often omitted	First-class reports & plots
Explainability	One-off SHAP cells	Integrated SHAP artifacts
Sharing with students/labs	Environment drift	Docker Compose + Hub images
Clinical deployment	Out of scope	Also out of scope (research only)

When to keep the notebook

Exploratory EDA, one-off plots, and paper-specific analyses still belong in notebooks—export cohorts from the workbench and continue there.

When to use the framework

Teaching a full loop, comparing models under a fixed task, or documenting leakage and calibration for methods sections.

Also see: Alternatives to opaque clinical AutoML · Features