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Duration 14 hours
Course Outline
Foundations of Agentic AI in Healthcare
- Distinguishing agentic systems from tool-only LLM applications.
- Defining autonomy boundaries, policies, and the role of human oversight.
- Understanding the healthcare data environment and its constraints (including EHR, FHIR, and PHI).
Architecting Agent Workflows
- Integrating planning, memory, tool usage, and reflection loops.
- Applying prompt engineering, function/tool definitions, and action selection strategies.
- Managing state and employing orchestration patterns.
Retrieval-Augmented Agents
- Ingesting and chunking medical documentation effectively.
- Utilizing embeddings, vector stores, and assessing relevance.
- Ensuring response grounding and implementing citation strategies.
Healthcare Integration and Interoperability
- Essential FHIR/SMART concepts for agent connectivity.
- Processing structured and unstructured clinical data.
- Implementing eventing, API management, and audit trails.
Safety, Risk Management, and Governance
- Designing guardrails, red-teaming exercises, and fail-safe mechanisms.
- Managing PHI, de-identification processes, and access controls.
- Establishing human-in-the-loop review and escalation pathways.
Evaluation and Monitoring
- Conducting offline evaluations, creating golden sets, and defining KPIs.
- Detecting hallucinations and performing factuality checks.
- Enhancing observability, logging, and managing cost/latency.
Deployment Strategies and Practical Lab
- Choosing between API-based and on-prem model deployments.
- Developing a retrieval-augmented agent using LangChain, FastAPI, and ChromaDB.
- Simulating incident response and executing rollback procedures.
Conclusion and Future Directions
Requirements
- Foundational proficiency in Python programming.
- Practical experience with data analysis or Machine Learning workflows.
- Familiarity with healthcare data standards and concepts (such as EHR and FHIR).
Target Audience
- Healthcare data scientists and ML engineers.
- Teams in clinical informatics and digital health product development.
- IT leaders and innovation managers within the healthcare sector.
