Shielding sensitive medical imaging data

IF 18.8 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Gaoyang Liu, Chen Wang, Tian Xia
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引用次数: 0

Abstract

Differential privacy offers protection in medical image processing but is traditionally thought to hinder accuracy. A recent study offers a reality check on the relationship between privacy measures and the ability of an artificial intelligence (AI) model to accurately analyse medical images.

Abstract Image

Abstract Image

屏蔽敏感的医学成像数据
差异化隐私在医学图像处理中提供了保护,但传统上被认为会妨碍准确性。最近的一项研究对隐私措施与人工智能(AI)模型准确分析医学图像的能力之间的关系进行了现实检验。
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来源期刊
CiteScore
36.90
自引率
2.10%
发文量
127
期刊介绍: Nature Machine Intelligence is a distinguished publication that presents original research and reviews on various topics in machine learning, robotics, and AI. Our focus extends beyond these fields, exploring their profound impact on other scientific disciplines, as well as societal and industrial aspects. We recognize limitless possibilities wherein machine intelligence can augment human capabilities and knowledge in domains like scientific exploration, healthcare, medical diagnostics, and the creation of safe and sustainable cities, transportation, and agriculture. Simultaneously, we acknowledge the emergence of ethical, social, and legal concerns due to the rapid pace of advancements. To foster interdisciplinary discussions on these far-reaching implications, Nature Machine Intelligence serves as a platform for dialogue facilitated through Comments, News Features, News & Views articles, and Correspondence. Our goal is to encourage a comprehensive examination of these subjects. Similar to all Nature-branded journals, Nature Machine Intelligence operates under the guidance of a team of skilled editors. We adhere to a fair and rigorous peer-review process, ensuring high standards of copy-editing and production, swift publication, and editorial independence.
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