Use of machine learning to develop and evaluate models using preoperative and intraoperative data to identify risks of postoperative complications

Authors

Bing Xue, Washington University in St. Louis
Dingwen Li, Washington University in St. Louis
Chenyang Lu, Washington University School of Medicine in St. Louis
Christopher R. King, Washington University School of Medicine in St. Louis
Troy Wildes, Washington University School of Medicine in St. Louis
Michael S. Avidan, Washington University School of Medicine in St. Louis
Thomas Kannampallil, Washington University School of Medicine in St. Louis
Joanna Abraham, Washington University School of Medicine in St. Louis

Journal

JAMA Network Open

Publication Date

2021

Volume

4

Issue

3

Last Page

e212240

Document Type

Open Access Publication

DOI

10.1001/jamanetworkopen.2021.2240

Rights and Permissions

Xue B, Li D, Lu C, et al. Use of Machine Learning to Develop and Evaluate Models Using Preoperative and Intraoperative Data to Identify Risks of Postoperative Complications. JAMA Netw Open. 2021;4(3):e212240. doi:10.1001/jamanetworkopen.2021.2240. This is an open access article distributed under the terms of the CC-BY License. © 2021 Xue B et al. JAMA Network Open.

Recommended Citation

Xue, Bing; Li, Dingwen; Lu, Chenyang; King, Christopher R.; Wildes, Troy; Avidan, Michael S.; Kannampallil, Thomas; and Abraham, Joanna, "Use of machine learning to develop and evaluate models using preoperative and intraoperative data to identify risks of postoperative complications." JAMA Network Open. 4, 3. - e212240. (2021).
https://digitalcommons.wustl.edu/open_access_pubs/10222