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机器学习在预测癌症患者围手术期结局中的应用:临床医生的叙述性综述。

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

机构信息

Division of Anesthesiology, Critical Care & Pain Medicine, The University of Texas at MD Anderson Cancer Center, Houston, TX 77030, USA.

Department of Colon & Rectal Surgery, The University of Texas at MD Anderson Cancer Center, Houston, TX 77030, USA.

出版信息

Curr Oncol. 2024 May 11;31(5):2727-2747. doi: 10.3390/curroncol31050207.

Abstract

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.

摘要

这篇叙述性评论探讨了机器学习 (ML) 和人工智能 (AI) 模型在增强围手术期癌症护理中的应用。ML 和 AI 模型通过预测结果和支持临床决策,为改善围手术期癌症护理提供了巨大的潜力。本综述针对围手术期专业人员,包括麻醉师、外科医生、重症监护医生、护士麻醉师和围手术期护士,提供了一个综合框架,用于整合 ML 和 AI 模型,以增强整个围手术期连续护理中的患者护理交付。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e252/11120613/1593d223b28e/curroncol-31-00207-g001.jpg

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