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

Machine Learning (2048) E-Health / Health Services Research and New Models of Care (711) Clinical Information and Decision Making (1890) Decision Support for Health Professionals (1515) Artificial Intelligence (2084) mHealth in a Clinical Setting (739) Clinical Decision Support for Anesthesiology (13)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/72602, first published .
Predicting Delayed Extubation After General Anesthesia in Postanesthesia Care Unit Patients Using Machine Learning: Model Development Study

Predicting Delayed Extubation After General Anesthesia in Postanesthesia Care Unit Patients Using Machine Learning: Model Development Study

Predicting Delayed Extubation After General Anesthesia in Postanesthesia Care Unit Patients Using Machine Learning: Model Development Study

Authors of this article:

Jianwei Luo1, 2 Author Orcid Image ;   Shaoman Lin1 Author Orcid Image ;   Liman Wang1 Author Orcid Image ;   Huanfan Ji2 Author Orcid Image ;   Jingcong Zheng2 Author Orcid Image ;   Tingkang Wang2 Author Orcid Image ;   Lin Chen2 Author Orcid Image ;   Ziqi Lin2 Author Orcid Image ;   Zhongqi Liu1 Author Orcid Image ;   Ning Liufu1 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Jianwei Luo   1, 2 * , BSN ;   Shaoman Lin   1 * , BSN ;   Liman Wang   1 * , BSN ;   Huanfan Ji   2 , BSN ;   Jingcong Zheng   2 , BSN ;   Tingkang Wang   2 , BSN ;   Lin Chen   2 , BSN ;   Ziqi Lin   2 , ADN ;   Zhongqi Liu   1 , MD ;   Ning Liufu   1 , MD

1 Department of Anesthesiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China

2 Department of Anesthesiology, Shenshan Medical Center, Memorial Hospital of Sun Yat-sen University, Shanwei, China

*these authors contributed equally

Corresponding Author:

  • Ning Liufu, MD
  • Department of Anesthesiology
  • Sun Yat-sen Memorial Hospital, Sun Yat-sen University
  • 107 Yanjiang West Road
  • Guangzhou 510120
  • China
  • Phone: 86 020-81332199
  • Email: liufn3@mail.sysu.edu.cn