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Clinical healthcare has been a natural application domain for ML with a few modest success stories of practical deployment. Inequity and healthcare disparity has long been a concern in clinical and public health for decades. However, the challenges of fair and equitable care using ML in health has largely remained unexplored. While a few works have attempted to highlight potential concerns and pitfalls in recent years, there are massive gaps in academic ML literature in this context. The goal of this workshop is to investigate issues around fairness that are specific to ML based healthcare. We hope to investigate a myriad of questions via the workshop.
Sat 9:00 a.m. - 9:15 a.m.
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Check-in and set up contributed posters
(Check-in)
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Sat 9:15 a.m. - 9:30 a.m.
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Opening Remarks
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Sat 9:30 a.m. - 10:00 a.m.
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Keynote - Milind Tambe
(Talk)
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Sat 10:00 a.m. - 10:30 a.m.
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Invited Talk - ZIad Obermeyer
(Talk)
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Ziad Obermeyer 🔗 |
Sat 10:30 a.m. - 11:00 a.m.
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Coffee Break and Poster Session
(Poster Session I)
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Rameswar Panda · Prasanna Sattigeri · Kush Varshney · Karthikeyan Natesan Ramamurthy · Harvineet Singh · Vishwali Mhasawade · Shalmali Joshi · Laleh Seyyed-Kalantari · Matthew McDermott · Gal Yona · James Atwood · Hansa Srinivasan · Yonatan Halpern · D. Sculley · Behrouz Babaki · Margarida Carvalho · Josie Williams · Narges Razavian · Haoran Zhang · Amy Lu · Irene Y Chen · Xiaojie Mao · Angela Zhou · Nathan Kallus
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Sat 11:00 a.m. - 12:45 p.m.
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Breakout Sessions
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Sat 12:45 p.m. - 2:00 p.m.
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Lunch Break
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Sat 2:00 p.m. - 2:30 p.m.
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Invited Talk - Sharad Goel
(Talk)
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Sat 2:30 p.m. - 3:00 p.m.
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Invited Talk - Noa Dagan/Noam Barda
(Talk)
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Noam Barda · Noa Dagan 🔗 |
Sat 3:00 p.m. - 3:30 p.m.
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Invited Talk - Chelsea Barabas
(Talk)
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Sat 3:30 p.m. - 4:00 p.m.
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Coffee Break and Poster Session
(Poster Session)
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Sat 4:00 p.m. - 5:00 p.m.
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Discussion Panel - All invited speakers will be panelists
(Discussion Panel)
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Sat 5:00 p.m. - 6:00 p.m.
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Spotlight Talks and Poster Session
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Author Information
Shalmali Joshi (Vector Institute)
Irene Y Chen (MIT)
Irene is a PhD student at MIT focusing on applications on health care and fairness. She did her undergrad at Harvard where I studied applied math and computational engineering. Before starting at MIT, she worked for two years at Dropbox as a data scientist and machine learning engineer.
Ziad Obermeyer (UC Berkeley School of Public Health)
Shems Saleh (Vector Institute)
Sendhil Mullainathan (University of Chicago)
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