From Model to Clinical Product
Most clinical ML work lives in notebooks. To matter, it has to cross the gap into clinical product:
- Clearly defined clinical decision point
- Integration into existing workflows (EHR, dashboards)
- Explainability and clinician trust
- Safety and validation in real-world settings
- Regulatory and compliance alignment
Use this page to expand on your perspective and reference specific case studies.