Healthcare

AI in Healthcare Agenda #

Healthcare Data – From Clinical Trials to Real-World Data #

  • AI in Healthcare – Clinical Data, Evaluations of AI Applications (Coursera – Stanford)
  • Clinical Data Science – Hands-on training in structured clinical data (EHR, OMOP, CDM), computational phenotyping, predictive modeling, and clinical NLP (Coursera – UColorado)
  • Hands-On Healthcare Data – Healthcare Informatics & Knowledge Graph (Book – Andrew Nguyen)

Causal Reasoning for Healthcare Decision #

  • A Crash Course in Causality – Inferring Causal Effects from Observational Data (Coursera – PennMed)
  • Causal AI – Structural Causal Models (SCMs) using DoWhy, enabling automated causal discovery, counterfactual reasoning, and intervention-based AI systems (altdeep.ai)

Knowledge-Driven Healthcare Decision #

  • Knowledge Graphs – Enabling structured reasoning for clinical decision support (Neo4j).
  • Knowledge Graph-Enhanced RAG – Combining structured medical knowledge with AI-driven retrieval to deliver context-aware, accurate, and explainable clinical insights (Neo4j with LangChain).

Regulatory Drivers of AI in Healthcare #

  • 21st Century Cures Act (2016)
  • FDA RWE Framework (2018)
  • CMS & ONC Interoperability Rule (2020)
  • FDA AI/ML SaMD Framework (2021)
  • FDA AI-Generated Synthetic Control Arms (2021)
  • HIPAA Updates for AI (2023)