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

Non-randomized Protocols and Methods (ehealth) (312) Clinical Information and Decision Making (491) Artificial Intelligence (336) Machine Learning (570) Decision Support for Health Professionals (417) Clinical Informatics (222)

Published on in Vol 10, No 7 (2021): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/27532, first published .
Predicting and Responding to Clinical Deterioration in Hospitalized Patients by Using Artificial Intelligence: Protocol for a Mixed Methods, Stepped Wedge Study

Predicting and Responding to Clinical Deterioration in Hospitalized Patients by Using Artificial Intelligence: Protocol for a Mixed Methods, Stepped Wedge Study

Predicting and Responding to Clinical Deterioration in Hospitalized Patients by Using Artificial Intelligence: Protocol for a Mixed Methods, Stepped Wedge Study

Authors of this article:

Laura M Holdsworth 1 Author Orcid Image ;   Samantha M R Kling 1 Author Orcid Image ;   Margaret Smith 1 Author Orcid Image ;   Nadia Safaeinili 1 Author Orcid Image ;   Lisa Shieh 1 Author Orcid Image ;   Stacie Vilendrer 1 Author Orcid Image ;   Donn W Garvert 1 Author Orcid Image ;   Marcy Winget 1 Author Orcid Image ;   Steven M Asch 1, 2 Author Orcid Image ;   Ron C Li 1 Author Orcid Image
Article Authors Cited by (1) Tweetations (4) Metrics

Journals

  1. Bose S, Greenstein J, Fackler J, Sarma S, Winslow R, Bembea M. Early Prediction of Multiple Organ Dysfunction in the Pediatric Intensive Care Unit. Frontiers in Pediatrics 2021;9 View