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A collection of the accepted abstracts for the Machine Learning for Health (ML4H) symposium 2021


Nov 30, 2021
Fabian Falck, Yuyin Zhou, Emma Rocheteau, Liyue Shen, Luis Oala, Girmaw Abebe, Subhrajit Roy, Stephen Pfohl, Emily Alsentzer, Matthew B. A. McDermott


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Counterfactual Reasoning for Fair Clinical Risk Prediction


Jul 14, 2019
Stephen Pfohl, Tony Duan, Daisy Yi Ding, Nigam H. Shah

* Machine Learning for Healthcare 2019 

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Predicting Inpatient Discharge Prioritization With Electronic Health Records


Dec 02, 2018
Anand Avati, Stephen Pfohl, Chris Lin, Thao Nguyen, Meng Zhang, Philip Hwang, Jessica Wetstone, Kenneth Jung, Andrew Ng, Nigam H. Shah


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The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data


Oct 04, 2018
Daisy Yi Ding, Chloé Simpson, Stephen Pfohl, Dave C. Kale, Kenneth Jung, Nigam H. Shah

* Pacific Symposium on Biocomputing (PSB) 2019, Hawaii, https://psb.stanford.edu/psb-online/; 13 pages, 7 figures; updated with the camera-ready version of the manuscript 

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Creating Fair Models of Atherosclerotic Cardiovascular Disease Risk


Sep 16, 2018
Stephen Pfohl, Ben Marafino, Adrien Coulet, Fatima Rodriguez, Latha Palaniappan, Nigam H. Shah


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