Predicting COVID-19 disease progression and patient outcomes based on temporal deep learning

Predicting COVID-19 disease progression and patient outcomes based on temporal deep learning

Abstract Background The coronavirus disease 2019 (COVID-19) pandemic has caused health concerns worldwide since December 2019. From the beginning of infection, patients will progress through different symptom stages, such as fever, dyspnea or even death. Identifying disease progression and predictin...

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Bibliographic Details
Main Authors: Chenxi Sun, Shenda Hong, Moxian Song, Hongyan Li, Zhenjie Wang
Format: Article
Language:English
Published: BMC 2021-02-01
Series:BMC Medical Informatics and Decision Making
Subjects:
COVID-19
Disease progression
Outcome early prediction
Irregularly sampled time series
Time-aware long short-term memory
Online Access:https://doi.org/10.1186/s12911-020-01359-9

Internet

https://doi.org/10.1186/s12911-020-01359-9

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