AI in Healthcare: From Design to Deployment and Oversight

Catalog description

This course trains students to plan, evaluate, and implement artificial intelligence (AI)- enabled decision support in real clinical settings. We cover the full lifecycle: problem framing; data specification; development choices; internal and external validation; clinical evaluation; deployment pathways; monitoring for dataset shift and performance drift; safety, equity, and governance; and health-system integration. We emphasize standards and guidance that shape real deployments: TRIPOD+AI reporting for prediction models, DECIDE-AI for early clinical evaluation, CONSORT-AI/SPIRIT-AI for trials, PROBAST+AI for risk-of-bias assessment, the National Institute of Standards and Technology (NIST) AI Risk Management Framework, and current United States regulatory and certification expectations for decision support and software as a medical device. Graded on A-F basis only. Credit Hour s : 3 Recommended: Graduate intro to biostatistics or epidemiology