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Development and Prospective Validation of a Machine Learning-Based Risk of Readmission Model in a Large Military Hospital.

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Bibliographic Details
Title: Development and Prospective Validation of a Machine Learning-Based Risk of Readmission Model in a Large Military Hospital.
Authors: Eckert C; KenSci Inc., Seattle, Washington, United States., Nieves-Robbins N; Office of the U.S. Army Surgeon General, Defense Health Headquarters (Health Information Technology/CMIO Office), Falls Church, Virginia, United States., Spieker E; Clinical Informatics Division, Madigan Army Medical Center, Joint Base Lewis-McChord, Tacoma, Washington, United States., Louwers T; KenSci Inc., Seattle, Washington, United States., Hazel D; KenSci Inc., Seattle, Washington, United States., Marquardt J; KenSci Inc., Seattle, Washington, United States., Solveson K; Clinical Informatics Division, Madigan Army Medical Center, Joint Base Lewis-McChord, Tacoma, Washington, United States., Zahid A; KenSci Inc., Seattle, Washington, United States., Ahmad M; KenSci Inc., Seattle, Washington, United States., Barnhill R; Clinical Informatics Division, Madigan Army Medical Center, Joint Base Lewis-McChord, Tacoma, Washington, United States., McKelvey TG; KenSci Inc., Seattle, Washington, United States., Marshall R; Clinical Informatics Division, Madigan Army Medical Center, Joint Base Lewis-McChord, Tacoma, Washington, United States., Shry E; Clinical Informatics Division, Madigan Army Medical Center, Joint Base Lewis-McChord, Tacoma, Washington, United States., Teredesai A; KenSci Inc., Seattle, Washington, United States.
Source: Applied clinical informatics [Appl Clin Inform] 2019 Mar; Vol. 10 (2), pp. 316-325. Date of Electronic Publication: 2019 May 08.
Publication Type: Journal Article; Research Support, U.S. Gov't, Non-P.H.S.; Validation Study
Journal Info: Publisher: Thieme Country of Publication: Germany NLM ID: 101537732 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1869-0327 (Electronic) Linking ISSN: 18690327 NLM ISO Abbreviation: Appl Clin Inform Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1869-0327
DOI:10.1055/s-0039-1688553