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B17 CheXpert++

Matthew McDermott
PhD Student at Massachusetts Institute of Technology
+ 4 speakers
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Machine Learning for Healthcare
August 7, 2020, Online, Los Angeles, CA, USA
Machine Learning for Healthcare
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About the talk

CheXpert++: Approximating the CheXpert labeler for Speed, Differentiability, and Probabilistic Output

00:15 Purpose

01:00 CheXpert++ Pipeline

02:10 Exploiting Inductive Bias via Active Learning

02:50 Active learning performance

About speakers

Matthew McDermott
PhD Student at Massachusetts Institute of Technology
Tzu Ming Harry Hsu
Deep Learning Engineer at Digital Drift Co
Wei-Hung Weng
Research Intern at Google
Marzyeh Ghassemi
Assistant Professor at University of Toronto
Peter Szolovits
Professor at MIT

Wei-Hung Weng is a PhD graduate at MIT EECS and Computer Science and Artificial Intelligence Laboratory. Prior to MIT, he received an MMSc degree in Biomedical Informatics from Harvard Medical School/Massachusetts General Hospital and MD from Chang Gung University (Taiwan). He also worked as a physician and pathologist for years. His research focuses on creating and applying machine learning algorithms for multimodal representation learning and reinforcement learning toward better clinical decision making.

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Please note that I am not a regular user of LinkedIn (or any other social networking site). Please do not be offended if I fail to respond to posts or connection requests. By far the best way to contact me if you have something specific to communicate about is by email.

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Matthew McDermott
Tzu Ming Harry Hsu
Wei-Hung Weng
Marzyeh Ghassemi
Peter Szolovits