数字化
互联网隐私
医学
数据共享
患者隐私
1998年数据保护法
隐私保护
大数据
信息隐私
伦理问题
新兴技术
验光服务
医疗保健
计算机科学
计算机安全
工程伦理学
替代医学
病理
数据挖掘
人工智能
政治学
法学
计算机视觉
工程类
作者
Yahan Yang,Wei Wang,Haotian Lin
出处
期刊:Current Opinion in Ophthalmology
[Ovid Technologies (Wolters Kluwer)]
日期:2024-08-27
标识
DOI:10.1097/icu.0000000000001087
摘要
Purpose of review Patient privacy protection is a critical focus in medical practice. Advances over the past decade in big data have led to the digitization of medical records, making medical data increasingly accessible through frequent data sharing and online communication. Periocular features, iris, and fundus images all contain biometric characteristics of patients, making privacy protection in ophthalmology particularly important. Consequently, privacy-preserving technologies have emerged, and are reviewed in this study. Recent findings Recent findings indicate that general medical privacy-preserving technologies, such as federated learning and blockchain, have been gradually applied in ophthalmology. However, the exploration of privacy protection techniques of specific ophthalmic examinations, like digital mask, is still limited. Moreover, we have observed advancements in addressing ophthalmic ethical issues related to privacy protection in the era of big data, such as algorithm fairness and explainability. Summary Future privacy protection for ophthalmic patients still faces challenges and requires improved strategies. Progress in privacy protection technology for ophthalmology will continue to promote a better healthcare environment and patient experience, as well as more effective data sharing and scientific research.
科研通智能强力驱动
Strongly Powered by AbleSci AI