Machine learning applied to multi-sensor information to reduce false alarm rate in the ICU.

Studies reveal that the false alarm rate (FAR) demonstrated by intensive care unit (ICU) vital signs monitors ranges from 0.72 to 0.99. We applied machine learning (ML) to ICU multi-sensor information to imitate a medical specialist in diagnosing patient condition. We hypothesized that applying this...

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Bibliographic Details

Published in:	Journal of Clinical Monitoring & Computing Vol. 34; no. 2; pp. 339 - 353
Main Authors:	Hever, Gal, Cohen, Liel, O'Connor, Michael F., Matot, Idit, Lerner, Boaz, Bitan, Yuval
Format:	equations & formulas research tables/charts Journal Article
Published:	Springer Nature Apr2020
Online Access:	View this record in EBSCOhost