干预放射学人工智能入门指南:第一部分 基础知识
Blair Edward Warren1,2, Alexander Bilbily1,3,4, Judy Wawira Gichoya5
1Department of Medical Imaging, University of Toronto, Toronto, ON, Canada.
人工智能 (AI) 为干预放射学 (IR) 提供了重大潜力. 了解人工智能的基本原理和拟议的分类系统可以帮助临床医生采用人工智能工具来改善患者护理.
科学领域:
- 放射学 放射学是一门学科.
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 人工智能 (AI) 正在迅速发展,对干预放射学 (IR) 有重大影响.
- 人工智能有限的正式培训对临床医生来说是一个障碍,影响了在临床环境中对人工智能技术的采用和信任.
- 对人工智能概念的熟悉对于干预放射科医生参与其开发和部署至关重要.
研究的目的:
- 为干预放射科医生提供AI的基础知识.
- 引入基于复杂性的AI模型的务实分类系统.
- 探索人工智能在干预放射学中的当前应用和实施模式.
主要方法:
- 对与临床实践相关的AI概念的审查.
- 为人工智能模型开发分类系统.
- 在程序前,程序内和程序后阶段对IR中AI实施的分析.
主要成果:
- 基础AI知识可以增强临床医生的理解和参与.
- 基于复杂性的分类系统可以指导AI评估.
- 人工智能正在IR程序的各个阶段实施.
结论:
- 对干预放射科医生来说,人工智能的基础教育是关键.
- 对AI分类的结构化方法可以促进其临床整合.
- 人工智能具有改造性的潜力,可以增强干预放射学实践.
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