Artificial Intelligence in Operating Room Management.
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...
| Publicado en: | Journal of Medical Systems Vol. 48; no. 1; pp. 1 - 17 |
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| Autores principales: | , , , , , |
| Formato: | research systematic review tables/charts Journal Article |
| Publicado: |
Springer Nature
2/14/2024
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=175895842&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 175895842 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: 2/14/2024 vid: 48 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 175895842 175895842 175895842 10.1007/s10916-024-02038-2 175895842 ppf: 1 ppct: 16 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Artificial Intelligence in Operating Room Management. aug: au: Bellini, Valentina Russo, Michele Domenichetti, Tania Panizzi, Matteo Allai, Simone Bignami, Elena Giovanna affil: https://ror.org/02k7wn190 Anesthesiology, Intensive Care and Pain Medicine Division, Department of Medicine and Surgery, University of Parma, 43126, Parma, Italy sug: subj: Operating Rooms Administration Machine Learning Utilization Health Resource Allocation Post Anesthesia Care Units Surgery Cancellations Treatment Duration Evaluation Prediction Models Perioperative Care Human Systematic Review Adult PubMed Embase Descriptive Statistics Linear Regression Confidence Intervals Logistic Regression Machine Learning Neural Networks (Computer) Length of Stay Decision Making Artificial Intelligence Utilization Adult: 19-44 years ab: 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. pubtype: Academic Journal doctype: research systematic review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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