Curriculum Map

AI & Clinical Decision Support

AI and machine learning in clinical practice. Covers clinical decision support systems, FDA regulation of AI/ML medical devices, algorithmic bias, liability and standard of care with AI, and the future of AI-augmented medicine.

6 Units

Early Units (Foundation)

Building Skills

Advanced Concepts

Capstone/Synthesis

AI and Machine Learning in Healthcare: Foundations and Applications

Examines the technical foundations of AI and machine learning in healthcare, including learning paradigms, neural network architectures, and current clinical applications.

20 minutes

Clinical Decision Support Systems: Design, Deployment, and Integration

Examines clinical decision support system architectures, evidence-based alert frameworks, medication safety interventions, and workflow integration strategies.

20 minutes

FDA Regulation of AI/ML Medical Devices: Pathways and Oversight

Examines FDA regulatory frameworks for AI/ML medical devices, including SaMD classification, 510(k) and PMA pathways, and the predetermined change control plan approach to algorithm updates.

20 minutes

Algorithmic Bias and Health Equity: Sources, Detection, and Mitigation

Examines sources of algorithmic bias in healthcare AI, documented disparities in algorithm performance, fairness measurement frameworks, and strategies for mitigating bias in clinical deployment.

20 minutes

Liability and Standard of Care with AI: Physician Responsibility in the Age of Algorithms

Examines medical malpractice implications of AI use in clinical practice, allocation of liability between clinicians and device manufacturers, the black box interpretability problem, and evolving standards of care.

20 minutes

The Future of AI in Clinical Practice: Transformation, Competency, and Accountability

Examines emerging applications of AI in autonomous diagnosis, precision medicine, and workflow transformation, and identifies professional competencies required for responsible AI integration in clinical practice.

20 minutes

Learning Progression

This course is designed to be taken sequentially. Earlier units establish foundational concepts that later units build upon. While you can explore units in any order, following the numbered sequence provides the most coherent learning experience.