AI+HEALTH 2026
AI+HEALTH brings together the people building, evaluating, and implementing AI in healthcare today.
Join us for Stanford's 6th annual virtual conference focused on AI in health and medicine. Hosted by the Stanford Center for Artificial Intelligence in Medicine and Imaging (AIMI), Stanford Institute for Human-Centered Artificial Intelligence (HAI), and Center for Continuing Medical Education (CME), AI+HEALTH convenes leaders from academia, healthcare, industry, and government for a broad and current view of the field.
The conference explores what those working across health AI need to know today, from how AI is being used, implemented, and evaluated in healthcare to the research and emerging technologies shaping what comes next. Through plenary sessions and four tracks, participants can engage with topics ranging from foundational concepts to clinical applications, implementation, and the evolving health AI landscape:
- The State of Health AI
- AI in Clinical Practice
- Implementing AI in Healthcare
- Foundations in Health AI
Event Details
Dates: December 8–9, 2026 from 8:00am-2:30pm PT
Location: Online
Early through Oct 31 | Regular Registration | |
|---|---|---|
| First 100 Registrants | $250 | Sold Out |
| Academic, Healthcare, Non-Profit, and Gov't * | $300 | $350 |
| Corporate/General * | $500 | $550 |
| Full-time Student/Trainee (requires verification) | $25 | $50 |
| Stanford Faculty/Staff** | $250 | $250 |
| * 10% group discount available for groups of 4 or more; applies to both early and regular registration rates. ** Register with Stanford STAP Funds here. Same early/regular registration rates for Stanford faculty/staff. | ||
Scholarships: A limited number of complimentary registrations are available for professionals working in AI and health who have financial need and would be unable to attend AI+HEALTH without support. To apply, click the Register Here button above and select Scholarship Applicant as the registration type. The deadline to apply is November 15, 2026.
Call for Abstracts
We invite submissions from professionals and trainees at Stanford and across the broader AI and health community for 5-minute lightning talks highlighting compelling work, ideas, and real-world experiences in AI and health. We welcome submissions related to clinical applications, implementation, research and emerging technologies, data, education, responsible AI, and other topics shaping the future of health AI.
Selected presenters will have the opportunity to share their work with a global audience of clinicians, researchers, healthcare leaders, and innovators. The program committee may also consider select submissions for other speaking opportunities within the AI+HEALTH program. Selected lightning talk presenters will receive 50% off conference registration. Full-time students and trainees will receive complimentary registration.
Preparing Your Submission
The submission form asks for presenter and institutional information, talk title, a brief 1–2 sentence description, and an abstract of up to 300 words. You’ll also be asked to identify the AI+HEALTH focus area and stage of work that best fit your submission, explain its relevance to AI+HEALTH attendees, and provide collaborators or co-authors, previous or upcoming presentations, and a link to relevant publications or other materials, if applicable.
Submission Deadline: Thursday, October 15, 2026, at 11:59pm PT
Accreditation
In support of improving patient care, Stanford Medicine is jointly accredited by the Accreditation Council for Continuing Medical Education (ACCME), the Accreditation Council for Pharmacy Education (ACPE), and the American Nurses Credentialing Center (ANCC), to provide continuing education for the healthcare team.
Credit Designation
American Medical Association (AMA) - Stanford Medicine designates this Live Activity for a maximum of 17 AMA PRA Category 1 CreditsTM. Physicians should claim only the credit commensurate with the extent of their participation in the activity. For more accreditation details, kindly refer to the Stanford CME website.