58 citations · 60 across the 3 of their papers we have counts for
7 papers
Characterizing the Value of Information in Medical Notes
Chao-Chun Hsu, Shantanu Karnwal, Sendhil Mullainathan +2
Machine learning models depend on the quality of input data. As electronic health records are widely adopted, the amount of data in health care is growing, along with complaints ab…
The Data Station: Combining Data, Compute, and Market Forces
Raul Castro Fernandez, Kyle Chard, Ben Blaiszik +7
This paper introduces Data Stations, a new data architecture that we are designing to tackle some of the most challenging data problems that we face today: access to sensitive data…
The Algorithmic Automation Problem: Prediction, Triage, and Human Effort
Maithra Raghu, Katy Blumer, Greg Corrado +3
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 predictio…
Measuring the Stability of EHR- and EKG-based Predictive Models
Andrew C. Miller, Ziad Obermeyer, Sendhil Mullainathan
Databases of electronic health records (EHRs) are increasingly used to inform clinical decisions. Machine learning methods can find patterns in EHRs that are predictive of future a…
A Probabilistic Model of Cardiac Physiology and Electrocardiograms
Andrew C. Miller, Ziad Obermeyer, David M. Blei +2
An electrocardiogram (EKG) is a common, non-invasive test that measures the electrical activity of a patient's heart. EKGs contain useful diagnostic information about patient healt…
Direct Uncertainty Prediction for Medical Second Opinions
Maithra Raghu, Katy Blumer, Rory Sayres +4
The issue of disagreements amongst human experts is a ubiquitous one in both machine learning and medicine. In medicine, this often corresponds to doctor disagreements on a patient…