生成语法
计算机科学
工作流程
人工智能
人工智能应用
德尔菲法
德尔菲
分级(工程)
专家系统
数据科学
最佳实践
管理科学
新兴技术
生成模型
自动化
知识管理
工程管理
深度学习
工作(物理)
计算机的法律问题
卫生技术
出处
期刊:PubMed
[National Institutes of Health]
日期:2026-05-11
卷期号:62 (5): 329-345
标识
DOI:10.3760/cma.j.cn112142-20250721-00317
摘要
With the rapid development of generative artificial intelligence (AI) technologies and large AI models, these technologies are expected to play an important role in multiple aspects of medical workflows in ophthalmology. However, their rapid and widespread adoption has also introduced multiple challenges regarding application specifications, ethical constraints, and legal compliance. To ensure the safe, effective, and compliant application of generative AI large models in ophthalmology, the Intelligent Ophthalmology Subcommittee (China) of Technical Committee on Smart Medical Digitalization of IEEE Technology and Engineering Management Society convened domestic experts in the field. Drawing upon relevant Chinese laws and regulations governing medical practice, data security, and privacy protection, and incorporating the latest research advances, the expert panel held multiple online and offline seminars nationwide. Using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system, Good Practice Statements, and the Delphi method, the panel developed a consensus framework addressing the ethical, technical, and legal issues associated with the application of generative AI large models in ophthalmology. Designed to be continuously updated as technology advances, this framework aims to provide evidence-based support for clinical practice.
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