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Call for Abstracts: Machine Learning + Healthcare Symposium in Bermuda

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SAIL: Symposium on Artificial Intelligence for Learning Health Systems (SAIL)

Location: Hamilton, Bermuda

Dates: April 27-29th, 2020

Website: https://sail.health/

Submission deadline: December 20th, 2019

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We are excited to announce the Symposium on Artificial Intelligence for Learning Health Systems (SAIL), a new annual international research symposium exploring the integration of artificial intelligence (AI) techniques into clinical medicine. SAIL, which will be held in Hamilton, Bermuda on April 27-29, 2020, will provide a forum for clinicians, machine learning researchers, and clinical informaticians to discuss approaches and challenges to using these approaches in the healthcare domain.

SAIL will feature invited presentations to expose AI practitioners to the clinical workflow and administrative challenges that commonly prevent real-world adoption. Panels will convene seasoned leaders who have overseen the implementation, adoption, and regulation of real clinical AI systems in practice. Tutorials will provide hands-on exposure to open-source tools for integrating apps with hospital IT systems. Finally, we solicit abstracts for podium or poster presentations designed to generate fruitful discussion (and debate!) among conference attendees from diverse backgrounds (clinicians, clinical informaticians, computer scientists, payors, and regulators).

We invite submissions for abstracts, which will be selected for podium and poster presentations. Abstracts may contain either: 1) new and unpublished work, 2) highlights of recently published work or 3) overarching research theses.

Research themes include: integrating AI into clinical workflows, deploying machine learning systems at scale, and methods for evaluation and monitoring of clinical ML systems. Topics of particular interest include fairness, privacy, generalizability across institutions over time, real-time prediction, and regulatory compliance. Descriptions of novel methods for real-world evidence, causal inference, and precision medicine are also welcome. We highly encourage work that involves interdisciplinary collaboration across AI researchers, clinicians, and informaticians.

Abstract submission deadline is December 20, 2019. Abstracts have a 500 word limit, excluding references, figures, and figure captions. Student discounts and travel support are available. See more details at https://sail.health/call_for_papers.html!

Organizers: Harvard Medical School, MIT, Johns Hopkins University, Columbia University, Duke University, Penn Medicine

Sponsors: New England Journal of Medicine, United Health Group

submitted by /u/samfin55
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.