This paper is in the following e-collection/theme issue:

Theme Issue 2022: Health Natural Language Processing and Applications (CHIP) (27) Machine Learning (1627) Decision Support for Health Professionals (1287)

Published on in Vol 10, No 10 (2022): October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37484, first published .
Identifying Patients With Heart Failure Who Are Susceptible to De Novo Acute Kidney Injury: Machine Learning Approach

Identifying Patients With Heart Failure Who Are Susceptible to De Novo Acute Kidney Injury: Machine Learning Approach

Identifying Patients With Heart Failure Who Are Susceptible to De Novo Acute Kidney Injury: Machine Learning Approach

Authors of this article:

Caogen Hong1, 2 Author Orcid Image ;   Zhoujian Sun3 Author Orcid Image ;   Yuzhe Hao2 Author Orcid Image ;   Zhanghuiya Dong2 Author Orcid Image ;   Zhaodan Gu2 Author Orcid Image ;   Zhengxing Huang4 Author Orcid Image
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New JMIR MedInform: Identifying #patients With Heart Failure Who Are Susceptible to De Novo Acute Kidney Injury: Ma… https://t.co/T0blxwqF8a

2:34 PM · Oct 14, 2022

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RT @jmirpub: New JMIR MedInform: Identifying #patients With Heart Failure Who Are Susceptible to De Novo Acute Kidney Injury: Machine Learn…

2:35 PM · Oct 14, 2022

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Identifying Patients With Heart Failure Who Are Susceptible to De Novo Acute Kidney Injury: Machine Learning Approach https://t.co/pMclHMv8S4 #arkgroup

5:48 PM · Oct 17, 2022

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