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Stanford AI in Healthcare Leadership and Strategy is a four-week hybrid program for healthcare leaders. It covers AI strategy, governance, model performance and safety, clinical and operational value, implementation, change management, and responsible scaling of AI solutions in healthcare.
MIT OCW 6.S897 Machine Learning for Healthcare introduces clinical data and machine learning for risk stratification, disease progression modeling, precision medicine, diagnosis, subtype discovery, medical imaging, public health, and clinical workflow improvement.
MIT OCW HST.953 focuses on practical considerations for operationalizing machine learning in healthcare settings. It is relevant for learners moving from clinical data modeling into visualization, deployment, workflow, and real-world healthcare AI implementation.
This University of Colorado System course introduces how AI shapes modern health systems, including key applications, adoption trends, digital transformation, health equity, and opportunities for addressing grand healthcare challenges. Coursera lists it as beginner level and 8 hours.
The Broad Institute ML4H Clinical AI Seminar Series features talks from leading experts at the intersection of AI and medicine. Topics include generative and foundation models, ethical and responsible AI, self-supervised learning, medical imaging, digital twins, and real-world clinical applications.