An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department
Abstract During the coronavirus disease 2019 (COVID-19) pandemic, rapid and accurate triage of patients at the emergency department is critical to inform decision-making. We propose a data-driven approach for automatic prediction of deterioration risk using a deep neural network that learns from che...
Main Authors: | Farah E. Shamout, Yiqiu Shen, Nan Wu, Aakash Kaku, Jungkyu Park, Taro Makino, Stanisław Jastrzębski, Jan Witowski, Duo Wang, Ben Zhang, Siddhant Dogra, Meng Cao, Narges Razavian, David Kudlowitz, Lea Azour, William Moore, Yvonne W. Lui, Yindalon Aphinyanaphongs, Carlos Fernandez-Granda, Krzysztof J. Geras |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Publishing Group
2021-05-01
|
Series: | npj Digital Medicine |
Online Access: | https://doi.org/10.1038/s41746-021-00453-0 |
Similar Items
-
IDENTIFYING HIGH QUALITY MEDLINE ARTICLES AND WEB SITES USING MACHINE LEARNING
by: Aphinyanaphongs, Yindalon
Published: (2007) -
Development, implementation, and prospective validation of a model to predict 60-day end-of-life in hospitalized adults upon admission at three sites
by: Vincent J. Major, et al.
Published: (2020-09-01) -
Predicting childhood obesity using electronic health records and publicly available data.
by: Robert Hammond, et al.
Published: (2019-01-01) -
Correction: Predicting childhood obesity using electronic health records and publicly available data.
by: Robert Hammond, et al.
Published: (2019-01-01) -
A validated, real-time prediction model for favorable outcomes in hospitalized COVID-19 patients
by: Narges Razavian, et al.
Published: (2020-10-01)