Validation of an Automatic Tagging System for Identifying Respiratory and Hemodynamic Deterioration Events in the Intensive Care Unit.

Danielle Jeddah^1,2, Ofer Chen², Ari M Lipsky^2,3, Andrea Forgacs², Gershon Celniker², Craig M Lilly^4,5,6, Itai M Pessach¹

¹The Chaim Sheba Medical Center, Tel-Hashomer and the Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel.

²Clew Medical Ltd., Netanya, Israel.

³Department of Emergency Medicine, Rambam Health Care Campus, Haifa, Israel.

⁴Departments of Medicine, Anesthesiology and Surgery, University of Massachusetts Medical School, Worcester, MA, USA.

⁵Clinical and Population Health Research Program, Graduate School of Biomedical Sciences, University of Massachusetts Medical School, Worcester, MA, USA.

⁶UMass Memorial Health Care, UMass Memorial Medical Center, Worcester, MA, USA.

PubMed PMC DOI PDF

Abstract

OBJECTIVE: Predictive models for critical events in the intensive care unit (ICU) might help providers anticipate patient deterioration. At the heart of predictive model development lies the ability to accurately label significant events, thereby facilitating the use of machine learning and similar strategies. We conducted this study to establish the validity of an automated system for tagging res…

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