Development and structure of an accurate machine learning algorithm to predict inpatient mortality and hospice outcomes in the coronavirus disease 2019 era

Authors

Stephen Chi, Washington University School of Medicine in St. Louis
Aixia Guo, Washington University School of Medicine in St. Louis
Kevin Heard, Washington University School of Medicine in St. Louis
Seunghwan Kim, Washington University School of Medicine in St. Louis
Randi Foraker, Washington University School of Medicine in St. Louis
Patrick White, Washington University School of Medicine in St. Louis
Nathan Moore, Washington University School of Medicine in St. Louis

Journal

Medical Care

Publication Date

5-1-2022

Volume

60

Issue

5

First Page

381

Last Page

386

Document Type

Open Access Publication

DOI

10.1097/MLR.0000000000001699

Rights and Permissions

Chi S, Guo A, Heard K, Kim S, Foraker R, White P, Moore N. Development and Structure of an Accurate Machine Learning Algorithm to Predict Inpatient Mortality and Hospice Outcomes in the Coronavirus Disease 2019 Era. Med Care. 2022 May 1;60(5):381-386. doi.org/10.1097/MLR.0000000000001699 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0/

Recommended Citation

Chi, Stephen; Guo, Aixia; Heard, Kevin; Kim, Seunghwan; Foraker, Randi; White, Patrick; and Moore, Nathan, "Development and structure of an accurate machine learning algorithm to predict inpatient mortality and hospice outcomes in the coronavirus disease 2019 era." Medical Care. 60, 5. 381 - 386. (2022).
https://digitalcommons.wustl.edu/open_access_pubs/11828