一个临床医生指南共享数据用于眼科人工智能
Nayoon Gim1,2,3, Yue Wu1,2, Marian Blazes1,2
1Department of Ophthalmology, University of Washington, Seattle, WA, United States.
Investigative ophthalmology & visual science
|June 12, 2024
概括
本综述探讨了眼科人工智能 (AI) 数据共享方法. 它比较了传统和新的方法,突出了确保数据隐私和医学伦理AI发展的战略.
科学领域:
- 眼科医生 眼科 眼科
- 医疗人工智能 医疗人工智能
- 数据科学数据科学数据科学
背景情况:
- 人工智能模型的性能严重依赖于数据质量,数量和多样性.
- 眼科为人工智能应用提供丰富的数据 (成像,记录,眼睛跟踪).
- 医疗数据共享面临着重大的隐私和监管障碍.
研究的目的:
- 审查医学中传统和非传统的数据共享方法.
- 专注于眼科中的应用和考虑.
- 引导研究人员在道德医学人工智能开发方面进行研究.
主要方法:
- 探索传统的数据传输技术.
- 分析新的隐私保护方法 (衍生数据集,安全环境,模型对数据).
- 审查现有的眼科文献关于数据共享.
主要成果:
- 传统方法涉及直接数据传输.
- 非传统的方法优先考虑安全和隐私.
- 不同的方法为医疗数据共享提供了不同的优点和缺点.
结论:
- 关于数据共享的知情决策对于医疗AI至关重要.
- 坚持道德标准和患者隐私是最重要的.
- 了解各种数据共享策略可以增强眼科人工智能开发.
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