Application of Machine Learning in Predicting Perioperative Outcomes in Patients with Cancer: A Narrative Review for Clinicians.

This narrative review explores the utilization of machine learning (ML) and artificial intelligence (AI) models to enhance perioperative cancer care. ML and AI models offer significant potential to improve perioperative cancer care by predicting outcomes and supporting clinical decision-making. Tail...

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Publicado en:Current Oncology Vol. 31; no. 5; pp. 2727 - 2748
Autores principales: Brydges, Garry, Uppal, Abhineet, Gottumukkala, Vijaya
Formato: Journal Article
Publicado: MDPI May2024
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Application of Machine Learning in Predicting Perioperative Outcomes in Patients with Cancer: A Narrative Review for Clinicians.
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          Brydges, Garry
          Uppal, Abhineet
          Gottumukkala, Vijaya
        affil: Division of Anesthesiology, Critical Care & Pain Medicine, The University of Texas at MD Anderson Cancer Center, Houston, TX 77030, USA
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      ab: This narrative review explores the utilization of machine learning (ML) and artificial intelligence (AI) models to enhance perioperative cancer care. ML and AI models offer significant potential to improve perioperative cancer care by predicting outcomes and supporting clinical decision-making. Tailored for perioperative professionals including anesthesiologists, surgeons, critical care physicians, nurse anesthetists, and perioperative nurses, this review provides a comprehensive framework for the integration of ML and AI models to enhance patient care delivery throughout the perioperative continuum.
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      doctype: Journal Article
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    language: English
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