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一个外科医生指南机器学习.

Daniel T Lammers1, Carly M Eckert2, Muhammad A Ahmad3

  • 1From the Department of Surgery, Madigan Army Medical Center, Tacoma, WA.

Annals of surgery open : perspectives of surgical history, education, and clinical approaches
|August 28, 2023
PubMed
概括
此摘要是机器生成的。

机器学习 (ML) 为寻找模式提供先进的数据建模,扩大其在医疗保健和外科手术中的应用. 对临床医生和研究人员来说,了解ML的原则,应用和局限性至关重要.

关键词:
人工智能的人工智能是人工智能.机器学习是机器学习.手术 手术 手术 手术 手术 手术 手术

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科学领域:

  • 计算机科学 计算机科学
  • 医疗信息学 医疗信息学

背景情况:

  • 机器学习 (ML) 涵盖了与传统统计方法不同的先进数据建模技术.
  • ML是一种人工智能的子集,专注于使用复杂算法识别模式.
  • 在医疗保健领域,ML的应用正在迅速增长,影响临床实践.

研究的目的:

  • 为外科医生提供应用机器学习的基础知识.
  • 引导临床医生实施和研究应用ML技术.
  • 促进涉及ML的科学出版物的批判性审查.

主要方法:

  • 本书介绍了机器学习的核心概念和原则.
  • 它概述了与外科实践相关的常见ML应用.
  • 讨论了研究和出版物审查的考虑因素.

主要成果:

  • 临床医生可以通过本小册子获得加速对ML的介绍.
  • 内容旨在消除ML的神秘性,将其与科幻小说中对AI的描绘分开.
  • 提供了在手术中适当实施和评估ML的基本知识.

结论:

  • 对于外科专业人士来说,掌握ML原则,应用和局限性至关重要.
  • 本资源是指导外科医生在实践和研究中使用ML的指南.
  • 提高对ML的理解有助于将其负责任地纳入医疗保健.