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.
On June 25, 2020, attendees of the inaugural AI in Health event heard from some of our province’s most talented medical professionals and leading AI researchers, including:
Which Liver Patients to Waitlist for a New Liver: Motivating A Novel Survival Prediction Model and Evaluation Measure
Deciding 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.
Apr 7th 2021
On March 26, Amii's Dustin Morrill, Ph.D. candidate at the University of Alberta, presented “Hindsight Rationality and Deviation Types in EFGs.”
Apr 1st 2021
On March 12, Kamalika Chaudhuri, Assistant Professor at the Computing Science & Engineering Department at the University of California San Diego, presented “New Case-Studies in Inferential and Differential Privacy.”
Mar 23rd 2021
The AI CoE is collaborating with Answer ALS and EverythingALS to launch an initiative called the End ALS Challenge, with the support of ALS Society of Canada, Ontario Brain Institute (OBI) and NetraMark Corp. The goal is to surface insights through an open data competition that connects the global AI and neuroscience communities to better understand the overall biology of amyotrophic lateral sclerosis (ALS), and improve diagnosis and drug discovery for ALS patients.
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