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

Clinical Information and Decision Making (1340) Decision Support for Health Professionals (1147) Artificial Intelligence (1216) Machine Learning (1401) Clinical Informatics (919)

Published on in Vol 24, No 12 (2022): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41819, first published .
A Machine Learning-Based Approach to Predict Prognosis and Length of Hospital Stay in Adults and Children With Traumatic Brain Injury: Retrospective Cohort Study

A Machine Learning-Based Approach to Predict Prognosis and Length of Hospital Stay in Adults and Children With Traumatic Brain Injury: Retrospective Cohort Study

A Machine Learning-Based Approach to Predict Prognosis and Length of Hospital Stay in Adults and Children With Traumatic Brain Injury: Retrospective Cohort Study

Authors of this article:

Cheng Fang1 Author Orcid Image ;   Yifeng Pan2 Author Orcid Image ;   Luotong Zhao1 Author Orcid Image ;   Zhaoyi Niu1 Author Orcid Image ;   Qingguo Guo1 Author Orcid Image ;   Bing Zhao1 Author Orcid Image
Article Authors Cited by (10) Tweetations (4) Metrics

Cheng Fang   1 * , MM ;   Yifeng Pan   2 * , MSE ;   Luotong Zhao   1 , MM ;   Zhaoyi Niu   1 , MM ;   Qingguo Guo   1 , MM ;   Bing Zhao   1 , MD

1 Department of Neurosurgery, The Second Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China

2 The School of Big Data and Artificial Intelligence, Anhui Xinhua University, Hefei, China

*these authors contributed equally

Corresponding Author:

  • Bing Zhao, MD
  • Department of Neurosurgery
  • The Second Affiliated Hospital of Anhui Medical University
  • Anhui Medical University
  • No. 678, Furong Raod
  • Hefei, 230601
  • China
  • Phone: 86 138 6611 2073
  • Fax: 86 0551 63869400
  • Email: aydzhb@126.com