Application of Machine Learning Models to Biomedical and Information System Signals From Critically Ill Adults.

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Bibliographic Details
Title: Application of Machine Learning Models to Biomedical and Information System Signals From Critically Ill Adults.
Authors: Lilly CM; Department of Medicine, UMass Memorial Medical Center, Worcester, MA; UMass Memorial Health, UMass Memorial Medical Center, Worcester, MA; Department of Anesthesiology and Surgery, University of Massachusetts, Worcester, MA; University of Massachusetts Chan Medical School, University of Massachusetts, Worcester, MA; Clinical and Population Health Research Program, University of Massachusetts, Worcester, MA; Graduate School of Biomedical Sciences, University of Massachusetts, Worcester, MA. Electronic address: craig.lilly@umassmed.edu., Kirk D; WakeMed Health & Hospitals, Raleigh/Cary, NC., Pessach IM; The Chaim Sheba Medical Center and Tel-Aviv University, Tel Hashomer, Israel; Clew Medical, Netanya, Israel., Lotun G; UMass Memorial Health, UMass Memorial Medical Center, Worcester, MA., Chen O; Clew Medical, Netanya, Israel., Lipsky A; The Chaim Sheba Medical Center and Tel-Aviv University, Tel Hashomer, Israel; Department of Emergency Medicine, Rambam Health Care Campus, Haifa, Israel., Lieder I; Clew Medical, Netanya, Israel., Celniker G; Clew Medical, Netanya, Israel., Cucchi EW; UMass Memorial Health, UMass Memorial Medical Center, Worcester, MA., Blum JM; Department of Anesthesiology, University of Iowa, Iowa City, IA.
Source: Chest [Chest] 2024 May; Vol. 165 (5), pp. 1139-1148. Date of Electronic Publication: 2023 Nov 01.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Country of Publication: United States NLM ID: 0231335 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1931-3543 (Electronic) Linking ISSN: 00123692 NLM ISO Abbreviation: Chest Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1931-3543
DOI:10.1016/j.chest.2023.10.036