AI in Healthcare & Biomedicine
Where the stakes are measured in outcomes, not accuracy
Clinical data reality, imaging and drug discovery, FDA pathways, domain shift, fairness, and why accuracy was never the metric.
Module
Clinical Data Reality
The EHR is a billing system that incidentally stores medicine — model accordingly
Module
Models in Medicine
Where AI actually ships — imaging workflow, and the drug discovery funnel
Module
Evidence, Not Demos
Calibration over accuracy, external validation, and fairness that survives contact
Module
Regulation, Privacy & Deployment
FDA pathways, HIPAA boundaries, silent pilots, and the lifecycle after go-live
Capstone project
Clinical AI assessment
Evaluate a real or hypothetical healthcare AI: what's the validation evidence, where could bias hide, and what does 'safe enough' mean for its use case?
Deliverable: An evaluation memo covering evidence, risks, and the approval bar you'd set.
Milestones
Finish every lesson to earn the AI in Healthcare & Biomedicine Certificate.