放射科医生和数据:我们是否增加了价值,或者数据只是数据?
Elliot K Fishman1, Philippe Soyer2, David B Hellmann3
1The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 600 North Wolfe Street, Baltimore, MD 21287, United States of America.
Clinical imaging
|April 19, 2025
概括
高质量的数据对于放射学中的人工智能至关重要. 医生参与数据策划和解释对于开发临床相关的人工智能模型至关重要,将数据视为公共利益.
科学领域:
- 放射学 放射学是一门学科.
- 人工智能的人工智能
- 医学数据科学 医学数据科学
背景情况:
- 放射学中的人工智能 (AI) 需要大量高质量的数据集.
- 数据的所有权和临床数据的二次使用是持续辩论的主题.
研究的目的:
- 为放射学中临床数据的二次使用提出框架.AI开发.
- 强调医生在创建临床相关的人工智能模型中的投入价值.
主要方法:
- 概念框架的发展.
- 关于放射学中的数据所有权和人工智能的文献综述.
- 数据作为公共利益的论证.
主要成果:
- 临床数据,当二次使用时,应该被视为公共利益.
- 医生的专业知识显著提高了人工智能数据的价值.
- 临床相关的AI模型依赖于精选和解释的数据.
结论:
- 医生投入对于开发有效的放射学AI是不可或缺的.
- 将临床数据视为公共利益,有助于人工智能的发展.
- 解决数据所有权是释放人工智能在医疗保健中的潜力的关键.
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