Join us for Stanford Health AI Week, a five-day series of events addressing the growing impact of artificial intelligence on research, medical training, and patient care.

Hosted by Stanford Medicine and Stanford University, the week convenes faculty, clinicians, researchers, policymakers, industry leaders, and students to explore AI’s promise, examine real-world use, and define a responsible path forward.

Included below is the schedule of events during Stanford Health AI Week and links to learn more. 


Schedule of Events:

Monday morning, June 1

AI For Mental Health (AI4MH): Foundations, Frontiers, and the Real World

Shaping AI’s role in mental health.

Monday afternoon, June 1

AI In MedEd Symposium

Exploring how artificial intelligence can responsibly enhance medical education across the continuum.

Details coming soon

Tuesday morning, June 2

RAISE Health Symposium

Charting AI's future in health and medicine.

Tuesday afternoon, June 2

AI in Life Sciences Symposium

Tracing the role of AI across the pharmaceutical lifecycle, from biomedical innovation to patient experience, focusing on how new capabilities can deliver meaningful impact.

Wednesday, June 3

AIMI Symposium: Artificial Intelligence in Medicine and Imaging

Showcasing groundbreaking research, real-world clinical applications, and critical discussions on translation and societal impact for AI in health and medicine.

Thursday morning, June 4

AIMI Academic x Industry Summit

Bringing academia and industry together in a forum to advance health AI from development to real-world impact.

Thursday afternoon, June 4

AIMI Pediatric Symposium: Artificial Intelligence in Medicine and Imaging

Showcasing groundbreaking research, real-world clinical applications, and critical discussions on translation AI to advance pediatric care.

Friday morning, June 5

AI Across the Translational Spectrum: From Discovery to Community Impact

A Clinical Translational Science Awards (CTSA) symposium highlighting how AI accelerates translational research, using digital twins as a unifying framework from discovery through evaluation to community impact.



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