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

Theme Issue 2022: Health Natural Language Processing and Applications (CHIP) (26) Machine Learning (960) Decision Support for Health Professionals (701)

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 Hong 1, 2 Author Orcid Image ;   Zhoujian Sun 3 Author Orcid Image ;   Yuzhe Hao 1 Author Orcid Image ;   Zhanghuiya Dong 1 Author Orcid Image ;   Zhaodan Gu 1 Author Orcid Image ;   Zhengxing Huang 4 Author Orcid Image
Article Authors Cited by Tweetations (2) Metrics
Caogen Hong 1, 2 , MSc ;   Zhoujian Sun 3 , PhD ;   Yuzhe Hao 1 , MSc ;   Zhanghuiya Dong 1 , MSc ;   Zhaodan Gu 1 , MSc ;   Zhengxing Huang 4 , PhD

1 Jiangsu Automation Research Institute , Lianyungang , CN

2 College of Biomedical Engineering and Instrument Science , Zhejiang University , Hangzhou , CN

3 Research Center for Applied Mathematics and Machine Intelligence , Zhejiang Lab , Hangzhou , CN

4 College of Computer Science and Technology , Zhejiang University , Hangzhou , CN

Corresponding Author:

  • Zhoujian Sun, PhD
  • Research Center for Applied Mathematics and Machine Intelligence
  • Zhejiang Lab
  • Kechuang Ave, Zhongtai Subdistrict, Yuhang District
  • Hangzhou
  • CN
  • Phone: 86 571 56390515
  • Email: sunzj@zhejianglab.edu.cn