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Task-Specific Evaluation for Healthcare AI Systems

7 chapters · 31 lessons

1. 1. Task-Specific Evaluation Fundamentals

   4 lessons

   Learn why generic benchmarks fail in healthcare and how to define evaluation criteria based on clinical task and risk.

2. 2. Failure Mode Analysis for Medical AI

   5 lessons

   Identify and categorize failure modes specific to healthcare applications, from hallucinations to inappropriate escalation.

3. 3. Grounding and Retrieval Evaluation

   4 lessons

   Assess how medical AI systems ground responses in approved content and handle knowledge currency requirements.

4. 4. Safety Constraints and Escalation Logic

   5 lessons

   Design evaluation protocols for uncertainty handling, scope boundaries, and appropriate handoff to human clinicians.

5. 5. Evaluating Patient Education Systems

   4 lessons

   Build evaluation frameworks for medical AI that explains conditions, treatments, and care instructions to patients.

6. 6. Evaluating Clinical Documentation and Support Tools

   4 lessons

   Assess AI systems that assist clinicians with note generation, summarization, and guideline retrieval.

7. 7. Building Continuous Evaluation and Governance Processes

   5 lessons

   Establish ongoing monitoring, incident response, and governance frameworks for deployed medical AI systems.