no code implementations • 5 Dec 2023 • Chao-Chun Hsu, Ziad Obermeyer, Chenhao Tan
Finally, the model indicates that notes written about Black and Hispanic patients have 12% and 21% higher predicted fatigue than Whites -- larger than overnight vs. daytime differences.
1 code implementation • Findings of the Association for Computational Linguistics 2020 • Chao-Chun Hsu, Shantanu Karnwal, Sendhil Mullainathan, Ziad Obermeyer, Chenhao Tan
Machine learning models depend on the quality of input data.
1 code implementation • 28 Mar 2019 • Maithra Raghu, Katy Blumer, Greg Corrado, Jon Kleinberg, Ziad Obermeyer, Sendhil Mullainathan
In a wide array of areas, algorithms are matching and surpassing the performance of human experts, leading to consideration of the roles of human judgment and algorithmic prediction in these domains.
no code implementations • 1 Dec 2018 • Andrew C. Miller, Ziad Obermeyer, David M. Blei, John P. Cunningham, Sendhil Mullainathan
An electrocardiogram (EKG) is a common, non-invasive test that measures the electrical activity of a patient's heart.
no code implementations • 1 Dec 2018 • Andrew C. Miller, Ziad Obermeyer, Sendhil Mullainathan
In a predictive task, we show that EKG-based models can be more stable than EHR-based models across different patient populations.
no code implementations • 4 Jul 2018 • Maithra Raghu, Katy Blumer, Rory Sayres, Ziad Obermeyer, Robert Kleinberg, Sendhil Mullainathan, Jon Kleinberg
Our central methodological finding is that Direct Uncertainty Prediction (DUP), training a model to predict an uncertainty score directly from the raw patient features, works better than Uncertainty Via Classification, the two-step process of training a classifier and postprocessing the output distribution to give an uncertainty score.
no code implementations • 2 Dec 2017 • Maggie Makar, Marzyeh Ghassemi, David Cutler, Ziad Obermeyer
Risk prediction is central to both clinical medicine and public health.