Clinical Informatics in Critical Care Medicine.

Clinical Decision Support Critical Care Informatics Knowledge Pyramid Machine Learning

Journal

The Yale journal of biology and medicine
ISSN: 1551-4056
Titre abrégé: Yale J Biol Med
Pays: United States
ID NLM: 0417414

Informations de publication

Date de publication:
09 2023
Historique:
medline: 3 10 2023
pubmed: 2 10 2023
entrez: 2 10 2023
Statut: epublish

Résumé

Continuous monitoring and treatment of patients in intensive care units generates vast amounts of data. Critical Care Medicine clinicians incorporate this continuously evolving data to make split-second, life or death decisions for management of these patients. Despite the abundance of data, it can be challenging to consider every accessible data point when making the quick decisions necessary at the point of care. Consequently, Clinical Informatics offers a natural partnership to improve the care for critically ill patients. The last two decades have seen a significant evolution in the role of Clinical Informatics in Critical Care Medicine. In this review, we will discuss how Clinical Informatics improves the care of critically ill patients by enhancing not only data collection and visualization but also bedside medical decision making. We will further discuss the evolving role of machine learning algorithms in Clinical Informatics as it pertains to Critical Care Medicine.

Identifiants

pubmed: 37780994
doi: 10.59249/WTTU3055
pii: yjbm963397
pmc: PMC10524812
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

397-405

Informations de copyright

Copyright ©2023, Yale Journal of Biology and Medicine.

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Auteurs

Girish N Nadkarni (GN)

Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Ankit Sakhuja (A)

Division of Cardiovascular Critical Care, Department of Cardiovascular and Thoracic Surgery, West Virginia University, Morgantown, WV, USA.

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Classifications MeSH