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Course Outline

Foundations of Agentic AI for Healthcare

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

Designing Agent Workflows

  • Implementing planning, memory, tool usage, and reflection loops
  • Prompt engineering, function/tool integration, and action selection
  • Managing state and orchestration patterns

Retrieval-Augmented Agents

  • Ingesting and chunking medical documents
  • Utilizing embeddings, vector stores, and relevance evaluation techniques
  • Ensuring grounded responses and implementing citation strategies

Healthcare Integrations and Interoperability

  • Mastering FHIR/SMART basics for agent connectivity
  • Processing structured and unstructured clinical data
  • Managing events, APIs, and audit trails

Safety, Risk, and Governance

  • Implementing guardrails, conducting red-teaming, and designing fail-safes
  • Handling PHI, de-identification processes, and access controls
  • Facilitating human-in-the-loop reviews and escalation paths

Evaluation and Monitoring

  • Conducting offline evaluations, utilizing golden sets, and defining KPIs
  • Detecting hallucinations and verifying factuality
  • Ensuring observability, logging, and managing cost/latency

Deployment Patterns and Hands-on Lab

  • Comparing API-based versus on-premises model options
  • Building a retrieval-augmented agent using LangChain, FastAPI, and ChromaDB
  • Simulating incident response and executing rollback procedures

Summary and Next Steps

Requirements

  • Foundational knowledge of Python programming
  • Practical experience with data analysis or machine learning workflows
  • Awareness of healthcare data standards (e.g., EHR, FHIR)

Target Audience

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

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