人工智能术语,方法和批判性评估:头痛临床医生和研究人员的入门教程
Gina M Dumkrieger1, Chia-Chun Chiang2, Pengfei Zhang3
1Department of Neurology, Mayo Clinic, Phoenix, Arizona, USA.
Headache
|December 11, 2024
概括
本综述为临床医生和研究人员提供了人工智能 (AI) 和机器学习 (ML) 在头痛医学中的指南. 了解人工智能基础是批判性地评估该领域的人工智能研究的关键.
科学领域:
- 人工智能 (AI) 是一种人工智能.
- 机器学习 (ML) 是指机器学习.
- 头痛 医学 医学 医学
背景情况:
- 人工智能在医疗保健中的应用,特别是头痛研究,正在迅速扩大.
- 头痛专家对人工智能发现的准确解释至关重要,但对于非专家来说具有挑战性.
- 这篇论文解决了头痛研究社区对人工智能素养的日益增长的需求.
研究的目的:
- 为头痛临床医生和研究人员提供AI和ML方法和评估的概述.
- 促进在头痛医学领域的跨学科沟通和研究.
- 增强对AI/ML头痛研究的理解和批判性评估.
主要方法:
- 对与头痛研究相关的基本AI/ML概念进行叙事审查.
- 来自头痛医学和人工智能领域的领导者的指导.
- 对人工智能术语,方法,应用,陷和偏见的关键参考文献的审查和引用.
主要成果:
- 解释AI模型创建,常见类型和评估方法.
- 人工智能在头痛医学中的应用例子.
- 讨论潜在的陷,伦理问题 (偏见,隐私,滥用) 和最近的研究.
结论:
- 在头痛医学中,AI/ML有许多有前途的当前和未来应用.
- 了解人工智能的基础知识使读者能够在背景下批判性地评估人工智能研究.
- 这篇论文旨在增加对AI/ML头痛研究进展的舒适度和批判性思维.
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