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Artificial Intelligence in Operating Room Management.

Authors :
Bellini, Valentina
Russo, Michele
Domenichetti, Tania
Panizzi, Matteo
Allai, Simone
Bignami, Elena Giovanna
Source :
Journal of Medical Systems. 2/14/2024, Vol. 48 Issue 1, p1-16. 16p.
Publication Year :
2024

Abstract

This systematic review examines the recent use of artificial intelligence, particularly machine learning, in the management of operating rooms. A total of 22 selected studies from February 2019 to September 2023 are analyzed. The review emphasizes the significant impact of AI on predicting surgical case durations, optimizing post-anesthesia care unit resource allocation, and detecting surgical case cancellations. Machine learning algorithms such as XGBoost, random forest, and neural networks have demonstrated their effectiveness in improving prediction accuracy and resource utilization. However, challenges such as data access and privacy concerns are acknowledged. The review highlights the evolving nature of artificial intelligence in perioperative medicine research and the need for continued innovation to harness artificial intelligence's transformative potential for healthcare administrators, practitioners, and patients. Ultimately, artificial intelligence integration in operative room management promises to enhance healthcare efficiency and patient outcomes. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01485598
Volume :
48
Issue :
1
Database :
Academic Search Index
Journal :
Journal of Medical Systems
Publication Type :
Academic Journal
Accession number :
175895842
Full Text :
https://doi.org/10.1007/s10916-024-02038-2