基于超声波的人工智能用于乳腺损伤的分类.
Ting Ma1, Zhen Wang2, Jian Dong2
1Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Frontiers in oncology
|March 16, 2026
概括
人工智能 (AI) 在乳房超声波查方面表现有前途,但临床翻译面临障碍. 需要严格的验证,以确保人工智能工具在现实环境中有效改善乳腺癌诊断.
科学领域:
- 医疗成像医学成像
- 人工智能的人工智能
- 在瘤学瘤学.
背景情况:
- 乳腺癌是女性最常见的癌症,因此早期检测至关重要.
- 乳房超声波是一个关键的查工具,特别是在密集的乳房.
- 目前的超声波方法由于操作员的依赖性和解释的可变性而面临限制.
研究的目的:
- 审查乳房超声波人工智能 (AI) 的最新进展.
- 批判性地分析将人工智能从研究转化为临床实践的挑战.
- 确定阻碍人工智能在现实世界中的有效性的方法限制.
主要方法:
- 这篇叙事综述综合了近期关于人工智能在乳房超声波中的研究.
- 它分析了技术进步,临床翻译障碍和实施策略.
- 该审查批判性地检查了人工智能研究中常见的方法缺陷.
主要成果:
- 人工智能展示了提高乳房超声波精度和效率的潜力.
- 临床验证存在重大差距,特别是在生成性AI和非质量损伤诊断方面.
- 对于商业人工智能系统,有限的多中心数据存在.
结论:
- 方法上的局限性,比如样本规模小,缺乏外部验证,往往会高估人工智能性能.
- 解决这些差距对于将基于证据的AI转化为临床实践至关重要.
- 本综述为乳腺癌诊断中严格的人工智能实施提供了见解.
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