Research : Medicine
“The Algorithmic Automation Problem: Prediction, Triage, and Human Effort,” with Maithra Raghu, Katy Blumer, Greg Corrado, Jon Kleinberg, and Ziad Obermeyer, 2019.
“A Probabilistic Model of Cardiac Physiology and Electrocardiograms,” joint with Andrew Miller, Ziad Obermeyer, David M. Blei, and John P. Cunnigham, arXiv preprint arXiv:1812.00209 (2018).
“Measuring the Stability of EHR- and EKG-based Predictive Models,” joint with Andrew C. Miller, Ziad Obermeyer, Sendhil Mullainathan Machine Learning for Health (NeurIPS Workshop), 2018
“A Machine Learning Approach to Low-Value Health Care: Wasted Tests, Missed Heart Attacks and Mis-Predictions,” with Ziad Obermeyer, 2019, NBER working paper 26168, National Bureau of Economics Research, Inc.
“Dissecting Racial Bias in an Algorithm Used to Manage the Health of Populations,” with Ziad Obermeyer, Brian Powers, and Christine Vogeli, Science, 366(6464), pp.447-453, 2019.
“Direct Uncertainty Prediction for Medical Second Opinions,” with Maithra Raghu, Katy Blumer, Jon Kleinberg, Rory Sayres, Ziad Obermeyer, and Robert Kleinberg, International Conference on Machine Learning (ICML), 2019.
“A Comparison of Patient History- and EKG-based Cardiac Risk Scores,” joint with Andrew C. Miller and Ziad Obermeyer, Proceedings of the AMIA Summit on Clinical Research Informatics (CRI), 2019
“Predictive Modeling of US Healthcare Spending in Late Life,” with Liran Einav, Amy Finkelstein and Ziad Obermeyer (2018), Science 29 Jun 2018: Vol. 360, Issue 6396, pp. 1462-1465. DOI: 10.1126/science.aar5045
“Individual differences in normal body temperature: longitudinal big data analysis of patient records,” with Obermeyer, Ziad, and Jasmeet K. Samra (2017), British Medical Journal 359
“Does Machine Learning Automate Moral Hazard and Error?” with Ziad Obermeyer (2017), American Economic Review, May 207, 107 (5): 476-80. (Non-refereed)