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Course Outline

Foundations of Agentic AI for Healthcare

  • Differentiating agentic systems from tool-only LLM applications.
  • Defining autonomy boundaries, policies, and the role of human oversight.
  • Understanding the healthcare data landscape and its constraints (EHR, FHIR, PHI).

Designing Agent Workflows

  • Implementing planning, memory, tool use, and reflection loops.
  • Techniques for prompt engineering, function/tool integration, and action selection.
  • Strategies for state management and orchestration patterns.

Retrieval-Augmented Agents

  • Processes for ingesting and chunking medical documents.
  • Utilizing embeddings, vector stores, and methods for relevance evaluation.
  • Ensuring response grounding and developing citation strategies.

Healthcare Integrations and Interoperability

  • Basics of FHIR/SMART for establishing agent connectivity.
  • Managing structured and unstructured clinical data.
  • Handling eventing, APIs, and maintaining audit trails.

Safety, Risk, and Governance

  • Implementing guardrails, conducting red-teaming, and designing fail-safes.
  • Managing PHI, applying de-identification techniques, and enforcing access controls.
  • Establishing human-in-the-loop review processes and escalation paths.

Evaluation and Monitoring

  • Conducting offline evaluations, utilizing golden sets, and defining KPIs.
  • Detecting hallucinations and performing factuality checks.
  • Ensuring observability, logging, and managing costs/latency.

Deployment Patterns and Hands-on Lab

  • Comparing API-based versus on-prem model options.
  • Constructing a retrieval-augmented agent using LangChain, FastAPI, and ChromaDB.
  • Practicing simulated incident response and rollback procedures.

Summary and Next Steps

Requirements

  • Foundational knowledge of Python programming.
  • Practical experience with data analysis or machine learning workflows.
  • Familiarity with healthcare data concepts, such as EHR and FHIR.

Target Audience

  • Healthcare data scientists and ML engineers.
  • Clinical informatics and digital health product teams.
  • IT leaders and innovation managers within the healthcare sector.
 14 Hours

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