This paper is in the following e-collection/theme issue:
Theme Issue: Medical Informatics and COVID-19 (107) JMIR Theme Issue: COVID-19 Special Issue (2461) Machine Learning (1501) Clinical Information and Decision Making (1434) Decision Support for Health Professionals (1210) Electronic Health Records (1068) Secondary Use of Clinical Data for Research and Surveillance (375) COVID-19 in an Elderly Population (15)Published on in Vol 10, No 3 (2022): March
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/32949, first published
.
Disease-Course Adapting Machine Learning Prognostication Models in Elderly Patients Critically Ill With COVID-19: Multicenter Cohort Study With External Validation
Disease-Course Adapting Machine Learning Prognostication Models in Elderly Patients Critically Ill With COVID-19: Multicenter Cohort Study With External Validation
Authors of this article:
Christian Jung1 ; Behrooz Mamandipoor2 ; Jesper Fjølner3 ; Raphael Romano Bruno1 ; Bernhard Wernly4 ; Antonio Artigas5 ; Bernardo Bollen Pinto6 ; Joerg C Schefold7 ; Georg Wolff1 ; Malte Kelm1 ; Michael Beil8 ; Sigal Sviri8 ; Peter V van Heerden9 ; Wojciech Szczeklik10 ; Miroslaw Czuczwar11 ; Muhammed Elhadi12 ; Michael Joannidis13 ; Sandra Oeyen14 ; Tilemachos Zafeiridis15 ; Brian Marsh16 ; Finn H Andersen17, 18 ; Rui Moreno19, 20 ; Maurizio Cecconi21 ; Susannah Leaver22 ; Dylan W De Lange23 ; Bertrand Guidet24, 25 ; Hans Flaatten26, 27 ; Venet Osmani2
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