Recurrent disease progression networks for modelling risk trajectory of heart failure.
<h4>Motivation</h4>Recurrent neural networks (RNN) are powerful frameworks to model medical time series records. Recent studies showed improved accuracy of predicting future medical events (e.g., readmission, mortality) by leveraging large amount of high-dimensional data. However, very f...
Main Authors: | Xing Han Lu, Aihua Liu, Shih-Chieh Fuh, Yi Lian, Liming Guo, Yi Yang, Ariane Marelli, Yue Li |
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Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2021-01-01
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Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0245177 |
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