2.7k citations · 2.7k across the 5 of their papers we have counts for
6 papers
A collection of invited non-archival papers for the Conference on Health, Inference, and Learning (CHIL) 2022
Gerardo Flores, George H. Chen, Tom Pollard +2
A collection of invited non-archival papers for the Conference on Health, Inference, and Learning (CHIL) 2022. This index is incomplete as some authors of invited non-archival pres…
Google COVID-19 Search Trends Symptoms Dataset: Anonymization Process Description (version 1.0)
Shailesh Bavadekar, Andrew Dai, John Davis +27
This report describes the aggregation and anonymization process applied to the initial version of COVID-19 Search Trends symptoms dataset (published at https://goo.gle/covid19sympt…
Modelling EHR timeseries by restricting feature interaction
Kun Zhang, Yuan Xue, Gerardo Flores +3
Time series data are prevalent in electronic health records, mostly in the form of physiological parameters such as vital signs and lab tests. The patterns of these values may be s…
Explaining an increase in predicted risk for clinical alerts
Michaela Hardt, Alvin Rajkomar, Gerardo Flores +5
Much work aims to explain a model's prediction on a static input. We consider explanations in a temporal setting where a stateful dynamical model produces a sequence of risk estima…
Learning the Graphical Structure of Electronic Health Records with Graph Convolutional Transformer
Edward Choi, Zhen Xu, Yujia Li +4
Effective modeling of electronic health records (EHR) is rapidly becoming an important topic in both academia and industry. A recent study showed that using the graphical structure…
Scalable and accurate deep learning for electronic health records
Alvin Rajkomar, Eyal Oren, Kai Chen +31
Predictive modeling with electronic health record (EHR) data is anticipated to drive personalized medicine and improve healthcare quality. Constructing predictive statistical model…