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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
  • Navigating the healthcare data landscape and its constraints (EHR, FHIR, PHI)

Designing Agent Workflows

  • Implementing planning, memory, tool use, and reflection loops
  • Leveraging prompt engineering, functions/tools, and action selection strategies
  • Mastering state management and orchestration patterns

Retrieval-Augmented Agents

  • Processing medical documents through ingestion and chunking techniques
  • Utilizing embeddings, vector stores, and relevance evaluation methods
  • Ensuring grounded responses and effective citation strategies

Healthcare Integrations and Interoperability

  • Understanding FHIR/SMART fundamentals for agent connectivity
  • Handling structured and unstructured clinical data effectively
  • Managing events, APIs, and maintaining comprehensive audit trails

Safety, Risk, and Governance

  • Implementing guardrails, red-teaming exercises, and fail-safe design principles
  • Managing PHI handling, de-identification processes, and access controls
  • Establishing human-in-the-loop review mechanisms and escalation paths

Evaluation and Monitoring

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

Deployment Patterns and Hands-on Lab

  • Comparing API-based versus on-prem model deployment 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
  • Prior experience with data analysis or machine learning workflows
  • Familiarity with key healthcare data concepts (e.g., EHR, FHIR)

Target Audience

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

Number of participants


Price per participant

Provisional Upcoming Courses (Require 5+ participants)

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