Program

Stop by the registration table to pick up your badge and program.

This session will discuss various clinical trial designs to generate robust scientific and statistical evidence of the clinical impact of an AI model. The session will begin with an overview of trial design for clinical AI models, cover advanced study designs such as stepped-wedge and cluster-randomized designs, and highlight these principles in real-world case studies, including the evaluation of AI scribes.

• Majid Afshar, University of Wisconsin
• Mary Beth Hamel, New England Journal of Medicine
• Patrick Heagerty, University of Washington

Even after receiving a genetic diagnosis, many rare disease patients face a prolonged and uncertain search for viable treatments. The Therapeutic Actionability AI Challenge invites teams to confront this gap by building automated systems, leveraging LLM agents and related AI technologies, that transform a patient’s genetic diagnosis into a personalized therapeutic actionability report. The competition unfolds in two phases: first, a question-answering phase built on a curated benchmark of challenging, real-world therapeutic decision edge case scenarios generated with input from functional genomics experts, clinicians, and genetic counselors; and second, full report generation. Cash prizes will be awarded to top-performing teams. Join us to hear about the challenge goals, how the benchmark is designed to reveal weaknesses in today’s biomedical AI systems, and ways to get involved.

• Samuel Finlayson, Seattle Children’s Hospital and University of Washington

There is still a big gap between what AI is supposed to deliver in healthcare and what it delivers in practice. Many tools don’t perform as expected once they’re deployed, or they never achieve the impact they were built for. This panel brings together leaders who have been through those hard lessons and will share candid examples of what went wrong and why. We will look at common failure modes–from technical problems (e.g., performance drift and weak generalization) to operational realities (e.g., workflow fit, integration pain, and clinician trust) to broader system issues (e.g., equity, transparency, and governance). The goal isn’t to dwell on failure; it’s to extract the lessons we need, to build AI that works in the real world.

• Carol Cain, Kaiser Permanente
• Muhammed Mamdani, Unity Health Toronto
• Hojjat Salmasian, University of Pennsylvania

Artificial intelligence is rapidly being integrated into healthcare, promising to improve patient safety, operational efficiency, and care quality. Yet as AI takes on increasingly complex clinical tasks, a critical question emerges: are we inadvertently eroding the very experiences that shape skilled, competent clinicians? Reduced exposure to diagnostic reasoning, procedural practice, and critical decision-making may have long-term consequences for the workforce we are training today. In this debate, we will challenge assumptions on both sides and ask whether we are even framing the right questions about AI and clinical competency.

• Sara Murray, University of California San Francisco
• Adam Rodman, Beth Israel Deaconess Medical Center

What really happens when AI meets patients at the point of care? In this fireside chat, a journalist, a health-tech executive, and patient advocates share candid, lived experiences of how AI shapes real-world care—at the front door, behind coverage decisions, and inside clinical workflows. Grounded in first-hand experience, this panel will explore how AI is designed and deployed in real-world settings and asks: whose values are these systems serving by default—and what would it take for them to more reliably reflect patients’ interests and human values?

• Megan Bent
• Ricky Bloomfield, Oura
• Casey Ross, STAT (moderator)
• Ellyn Winter-Robinson, The Lyndall Project

Mental health represents a particularly high-stakes use case for medical AI, as recent lawsuits implicating commercial tools in patient suicides have made painfully clear. Yet an equally pressing problem demands attention: a global shortage of qualified mental health providers has left millions without adequate care, and—advised or not—many are already turning to commercial chatbots for counseling and support. What safeguards are needed before deploying AI in these contexts, and who should be responsible for enforcing them? How should we design clinical trials when the risk of harm is acute and the affected population is vulnerable? And how do we balance regulatory caution against the reality that millions are already using unregulated tools? This panel will tackle these questions, bringing together experts in psychiatry, bioethics, algorithmic accountability, and the hands-on development and prospective evaluation of mental health AI systems.

• Nicholas Jacobson, Dartmouth 
• Roy Perlis, Massachusetts General Hospital
• Inioluwa Deborah Raji, University of California, Berkeley

Since showcasing the power of language model orchestration in clinical diagnostics with MAI-DxO last year, the health research team at Microsoft AI will share new progress on advanced clinical reasoning and improving the consumer experience of healthcare.

• Xiaoxuan Liu & Harsha Nori, Microsoft AI

Do we always need a trial to evaluate the clinical impact of an AI model? When is it safe to deploy without a trial? Are there truly effective ways to roll out model deployment in real-world settings and still have robust estimates of its clinical impact? Let’s debate!

• Anna Goldenberg, University of Toronto
• Patrick Heagerty, University of Washington

As large electronic health records and AI technology vendors increasingly dominate the healthcare landscape, how do venture capitalists, startups, and health systems navigate technology investment decisions? This panel brings together voices from across the ecosystem to uncover the tensions, trade-offs, and strategies at play when major incumbent vendors loom large over innovation and investment priorities in health AI. Panelists will explore how entrepreneurship can succeed in the presence of giants, what health systems weigh when choosing between building on dominant platforms versus betting on emerging players, and how the industry can foster an environment where transformative ideas still have room to thrive.

• Ashley Beecy, Sutter Health (moderator)
• Vivien Ho, OpenEvidence
• Aaron Neinstein, Notable
• Hong Truong, Define Ventures

This Year in Review session will explore key themes in AI deployment into the clinic over the past year, supported by notable papers and real-world case studies. We will discuss both highlights and lowlights, examining what has worked, what hasn’t, and why. Through a review of impactful research and major events, this session will provide a critical perspective on the state of clinical AI and where it is headed next.

• Jean Feng and Julian Hong, University of California San Francisco

The feasibility, safety, and promise of conversational diagnostic AI in real-world care. This presentation reports results from a pre-registered prospective study of the Articulate Medical Intelligence Explorer (AMIE) at a busy primary care clinic in Boston, MA. This presentation will focus not only on trial results, but on methodological lessons learned for those looking to safely launch patient-facing AI studies.

• Adam Rodman, Beth Israel Deaconess Medical Center

Safeguard now, or stifle breakthroughs? Two leading experts face off in a high-stakes debate. One side warns that without immediate, robust regulation, clinical AI will trigger widespread medical errors and privacy breaches at population scale. The other argues that regulating too soon will deny millions of patients the full power of today’s AI models—especially where human expertise is scarce—and slow the development of tomorrow’s truly high-performance systems. Which path protects patients more: faster guardrails or faster progress? Come decide with us at SAIL.

• Stephen Ball
• Brendan O’Leary

Surgical AI is rapidly transforming the operating room into a data-rich, learning environment. Robotic surgery, tele-operation, and augmented reality technologies are the new frontier of the interface that is now merging computer vision, language models, and robotic action models to augment surgical skill, safety, and awareness. Real-time analytics driven by machine perception can quantify surgical technique, guide intraoperative decision-making, and provide adaptive feedback to surgeons and trainees. Looking forward, integration of multimodal operative data with learning health system infrastructure will enable closed-loop improvement in surgical workflows, complication prevention, and patient outcomes. This session will explore how AI-augmented robotics and analytics can move surgery toward a measurable, continuously learning discipline that scales expertise and improves care at the system level.

• Nadine Hachach-Haram, Proximie
• Christopher Morley, Medivis

Join other SAIL attendees for a 2-hour kayak tour to experience the rare phenomenon of bioluminescence in Laguna Grande, one of 3 bio-bays found in Puerto Rico (and only 5 worldwide!). The glowing effect in the water is caused by dinoflagellates—microscopic organisms that emit a bluish-green neon glow in reaction to movement in the water. When planning your visit to this natural wonder, keep in mind that the glowing effect is better appreciated on dark nights, the later the better!

Plan to depart the hotel by 7:30 PM and arrive in Fajardo by 8:15 PM. Transportation must be arranged separately.

Only 25 spaces available – book by April 23rd. Call 787-245-4545 to buy tickets and reference booking number “335251337”. Go to https://kayakingpuertorico.com/home/tours/bio-bay-kayak-tour/ for more info.

($67 per person. Children under the age of 6 are not permitted.)

Join other SAIL attendees for a guided hike into the heart of Puerto Rico’s El Yunque rainforest. Hike through the lush foliage and learn more about the wildlife that calls El Yunque home. Next, swim in a natural pool, go cliff-diving and rope-swinging if you dare, and admire the waterfalls.

Plan to depart the hotel by 7:30 AM. Transportation included to/from hotel.

Limited spaces available. More details will be posted soon. Go to https://micasaventuras.com/el-yunque-rainforest-adventure.html for more info. ($77 per person. Children under the age of 2 are not permitted.)

Join other SAIL attendees for an unforgettable guided adventure that takes you off the beaten path to enjoy a 2.5 hour horseback ride, while taking in the Caribbean views and the beauty of the rainforest ecosystem. This tour takes you to the Mameyes River; in addition, you’ll have the opportunity to ride on one of the best known beaches in the Caribbean. This tour caters to all levels of riders: beginner, intermediate, and experienced riders are all welcome.

Plan to depart the hotel by 8:00 AM. Transportation must be arranged separately.

Limited spaces available. More details will be posted soon. Go to https://carabalirainforestpark.com/adventures/horseback-beach/ for more info. ($140 per person. Children under the age of 8 are not permitted.)