大数据在围手术期麻醉管理中的应用和前景

Yiziting Zhu, Xiang Liu, Yujie Li, Bin Yi
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引用次数: 0

摘要

围术期麻醉管理需要在复杂的医疗场景中做出大量决策。这就要求持续、动态地执行精确决策,从而带来了巨大的挑战。在大数据时代,来自不同来源的数据量呈指数级增长,给医疗保健、金融和营销等许多领域带来了革命性的变化。机器学习已成为分析大数据的强大工具,能够处理大型数据集,并揭示错综复杂的模式和关系。大数据与人工智能算法的应用逐渐融合,使围手术期管理各阶段的任务得以有效完成,包括风险预测、决策支持和辅助检查。通过对大数据的深入分析,医护人员可以洞察患者的预后。本综述全面概述了围术期大数据的显著特点及其在围术期麻醉管理中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The applications and prospects of big data in perioperative anesthetic management

Perioperative anesthetic management entails a multitude of decision-making processes within complex medical scenarios. These demand the continuous and dynamic execution of precise decisions which poses significant challenges. In the age of big data, the exponential growth in data volume from diverse sources has revolutionized many fields, including healthcare, finance, and marketing. Machine learning has emerged as a powerful tool for analyzing big data, enabling the handling of large datasets and uncovering intricate patterns and relationships. The application of big data and artificial intelligence algorithms is gradually being integrated, enabling effective task completion in various stages of perioperative management, including risk prediction, decision support, and auxiliary examination. Through in-depth analysis of big data, healthcare professionals can gain insights into patient prognoses. This review provides a comprehensive overview of the distinctive features of perioperative big data and its applications in anesthesia management during the perioperative period.

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