Deep representation learning from electronic medical records identifies distinct symptom based subtypes and progression patterns for COVID-19 prognosis-Reference-Cited by-同舟云学术

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Deep representation learning from electronic medical records identifies distinct symptom based subtypes and progression patterns for COVID-19 prognosis

Published:2024-11 Issue: Volume:191 Page:105555
ISSN:1386-5056
Container-title:International Journal of Medical Informatics
language:en
Short-container-title:International Journal of Medical Informatics

Author:

Zheng Qiguang,Shen Qifan,Shu Zixin,Chang Kai,Zhong Kunyu,Yan Yuhang,Ke Jia,Huang Jingjing,Su Rui,Xia Jianan,Zhou Xuezhong

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference45 articles.

1. The COVID-19 pandemic;Ciotti;Crit. Rev. Clin. Lab. Sci.,2020

2. COVID-19 and multiorgan response: the long-term impact;Harky;Curr. Probl. Cardiol.,2023

3. COVID-19 impact on public health, environment, human psychology, global socioeconomy, and education;Miyah;Scientific World J.,2022

4. Clinical features and the traditional Chinese medicine therapeutic characteristics of 293 COVID-19 inpatient cases;Shu;Front Med.,2020

5. Longitudinal symptom dynamics of COVID-19 infection;Mizrahi;Nat. Commun.,2020

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