an Juan Antiguo, San Juan, Puerto Rico

Symposium on Artificial Intelligence for Learning Health Systems

SAIL 2023

May 9–12, 2023

Puerto Rico

Symposium Updates

We are pleased to announce that SAIL 2023 will take place May 9–12, 2023, at the Hyatt Regency Grand Reserve, Río Grande, Puerto Rico. The complete SAIL 2023 program is now posted. In-person registration will open later in March, subject to space availability. You may register now to view livestreams of the keynote sessions:

  • Opening Keynote | Peter Lee, PhD (Corporate VP, Microsoft Research) | Wednesday, May 10 | 2:20–3:05pm ET
  • Closing Keynote | Nina Tousch (Owner & Founder, Glucose Toujours) | Friday, May 12 | 12:15–1:00pm ET

Key Dates

  • Nov 14, 2022: Call for Abstracts announced
  • Jan 9, 2023: Abstract submission and Travel Support application open
  • Jan 20, 2023: Abstracts & Travel Support applications due
  • Feb 24, 2023: Accepted Abstracts and Travel Support announced
  • March 2023: Registration opens
  • May 9-12, 2023: SAIL 2023 in Puerto Rico

NEJM Scholarships
The top four abstracts will be selected to receive a travel grant of $5,000 USD each from the New England Journal of Medicine.

SAIL 2022 Video Archive

  • Opening Keynote: Leveraging Autonomous AI to Solve Disparities in Healthcare (Michael Abramoff)
  • Fireside Chat: AI in Medical Publishing (editors of NEJM, Nature Medicine and The Lancet Digital Health)
  • Closing Keynote: Regulating AI in Healthcare: Now and into the Future (Amy Abernethy)


The Symposium on Artificial Intelligence for Learning Health Systems (SAIL) is an annual international conference launched in 2020 to explore the integration of artificial intelligence (AI) techniques into clinical medicine. SAIL, which will next be held in Puerto Rico in 2023, provides a forum for clinicians, clinical informaticians and AI researchers to discuss approaches and challenges to using these approaches in the healthcare domain.

Researchers from the fields of clinical informatics and machine learning have been concerned for decades with bridging the gap between quantitative research and clinical practice. Less appreciated, perhaps, is a potential disconnect between the communities of clinical informatics and machine learning researchers themselves. Clinical informaticians, for their part, have unique experience integrating their tools within hospital IT systems, and working with administrators, privacy policies, and quality improvement officers. Computer scientists, for their part, have frequently spearheaded the development of novel methodological tools and high-performance computing. Both of these research communities seek to work effectively with clinicians, who provide important domain expertise and interaction with patients. One explicit goal of this conference is to foster the translation of AI to the clinic by catalyzing collaborations that leverage the strengths of all three of these communities. A second goal is to facilitate discussion among diverse stakeholders- the three communities described above as well as funders and decision makers around the non-technical barriers to better care through AI. The inaugural Program Committee of SAIL was led by Jessie Tenenbaum (Duke), Jason Moore (UPenn), Nicholas Tatonetti (Columbia), Suchi Saria (Johns Hopkins), and Isaac Kohane (Harvard).

logos of inaugural committee members' home institutions

SAIL is supported by