AI in Health: the Future of Research and Application - June 25, 2020

One of Canada’s three centres of artificial intelligence excellence as part of the Pan-Canadian AI Strategy, Amii (the Alberta Machine Intelligence Institute) is an Alberta-based non-profit institute that supports world-leading research in artificial intelligence and machine learning and translates scientific advancement into industry adoption. Amii grows AI capabilities through advancing leading-edge research, delivering exceptional educational offerings and providing business advice – all with the goal of building in-house AI capabilities. For more information, visitamii.ca.

Alberta Machine Intelligence Institute (Amii)

Hear from medical professionals and AI experts as we explore research intersections and discuss the future of AI in healthcare!

Healthcare systems around the world are continually developing strategies to individualize care, improve outcomes and contain costs. Particularly, AI in healthcare is a burgeoning field, used today in applications such as diagnostic processes, treatment tools, drug discovery and development, remote patient monitoring and more.Join us for an exciting conversation and dive into homegrown breakthroughs and technologies that create real-world impact.Overview of the event:<ul><li>Opening remarks from Lawrence Richer MD, MSc, FRCPC – Academic Lead, Precision Health Signature Initiative, and Associate Dean, Clinical and Translational Research at the Faculty of Medicine &amp; Dentistry at the University of Alberta</li><li>Presentation from Dr. Russ Greiner</li><li>Closing remarks from Dr. Brenda Hemmelgarn  – Dean of the Faculty of Medicine &amp; Dentistry at the University of Alberta, and Cam Linke – CEO of the Alberta Machine Intelligence Institute (Amii)</li><li>Open forum for questions</li></ul>Feature presentation by Dr. Russ Greiner:Which Liver Patients to Waitlist for a New Liver: Motivating A Novel Survival Prediction Model and Evaluation MeasureDeciding which patient should be waitlisted for a liver transplant should depend on utility, the patient’s chance of long-term survival with the graft. However, most survival models use only risk scores, which are discriminative (can compare predicted outcomes between patients), but are not measuring the desired characteristic: utility for a single patient. This motivated us to develop and use a novel type of predictor that can produce an “Individual Survival Distribution” for each patient.This presentation first overviews standard survival analysis models to discuss what each can (and cannot) do, to motivate our approach. We then discuss the issue of evaluating these models, leading to a novel evaluation method (D-calibration). Finally, we show that this approach works effectively, leading to a deployed system to help hepatologists make this critical decision for their patients.Special thanks to the event partners:<a href="https://www.ualberta.ca/medicine" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">The University of Alberta Faculty of Medicine &amp; Dentistry</a><a href="https://www.roche.com/" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">Roche</a>

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AI in Health: the Future of Research and Application - June 25, 2020

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AI in Health: the Future of Research and Application - June 25, 2020

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