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

Theme Issue 2022: Health Natural Language Processing and Applications (CHIP) (27) Machine Learning (1824) Decision Support for Health Professionals (1390)

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
Article Authors Cited by (3) Tweetations (3) Metrics

Caogen Hong   1, 2 , MSc ;   Zhoujian Sun   3 , PhD ;   Yuzhe Hao   2 , MSc ;   Zhanghuiya Dong   2 , MSc ;   Zhaodan Gu   2 , MSc ;   Zhengxing Huang   4 , PhD

1 College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China

2 Jiangsu Automation Research Institute, Lianyungang, China

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

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

Corresponding Author:

  • Zhoujian Sun, PhD
  • Research Center for Applied Mathematics and Machine Intelligence
  • Zhejiang Lab
  • Kechuang Ave, Zhongtai Subdistrict, Yuhang District
  • Hangzhou 311121
  • China
  • Phone: 86 571 56390515
  • Fax: 86 518 85983716
  • Email: sunzj@zhejianglab.edu.cn