
收稿日期: 2025-05-05
录用日期: 2025-06-25
网络出版日期: 2025-09-30
基金资助
上海市卫生健康委员会卫生行业研究专项(20244Z0005);上海交通大学医学院“双百人”项目(20172018)
Research progress on intelligent diagnosis of eye diseases based on facial photos
Received date: 2025-05-05
Accepted date: 2025-06-25
Online published: 2025-09-30
Supported by
Shanghai Health Commission Research Special Fund for the Health Industry(20244Z0005);“Two-hundred Talents” Program of Shanghai Jiao Tong University School of Medicine(20172018)
我国眼病患者众多,眼病所致的视觉功能障碍、心理负担及社会参与受限等负面效应日益严峻。受限于医疗资源紧张与区域分布不均,且传统诊疗方式在准确性与效率方面存在显著局限性,开发敏感、高效的新型诊疗技术已成为迫切需求。随着人工智能技术的迅猛发展,眼科诊断领域迎来了智能化变革的新契机。作为一种无创、安全且便捷的信息载体,面部照片在眼病诊断中展现出独特优势。近年来,基于面部照片的人工智能系统已在近视、斜视、上睑下垂及甲状腺相关眼病等常见疾病的筛查与辅助诊断中得到初步应用,在提升筛查效率与诊断准确率方面表现出良好潜力。该文介绍了基于面部照片的眼病智能诊断流程,重点着眼于对近年来国内外相关研究成果的回顾,归纳基于面部照片的眼病智能诊断系统的创新点及应用优势,分析其当前面临的技术瓶颈与应用挑战,提出应对策略,并展望未来发展方向,以期为眼部疾病的智能化筛查与诊断提供参考与新思路。
胥瀚文 , 陈墨馨 , 梁小乙 , 舒琴 , 聂琬钦 , 杨雪峰 , 沈慜瑄 , 黎晓静 , 曹禹 , 李琳 . 基于面部照片的眼病智能诊断研究进展[J]. 上海交通大学学报(医学版), 2025 , 45(9) : 1249 -1255 . DOI: 10.3969/j.issn.1674-8115.2025.09.017
The number of patients with eye diseases in China is enormous, and the negative effects of these conditions, such as impaired visual function, psychological burdens, and restricted social participation, are becoming increasingly severe. Due to the limited and unevenly distributed ophthalmic resources, and the significant limitations of traditional diagnostic and therapeutic approaches in terms of accuracy and efficiency, there is an urgent need for more sensitive and efficient modalities. With the rapid advancement of artificial intelligence technology, ophthalmic diagnosis has entered a new stage of intelligent transformation. Facial photos, as a noninvasive and convenient medium, show unique advantages in eye disease diagnosis. Artificial intelligence systems based on facial photo analysis have been applied to the screening and diagnosis of conditions such as myopia, strabismus, ptosis, and thyroid eye disease, showing promising results. This review introduces the workflow of intelligent diagnosis for ocular diseases based on facial photographs, with a focus on recapitulating relevant research findings both domestically and internationally in recent years. It summarizes the innovative features and application advantages of intelligent diagnosis systems for eye diseases based on facial photos, analyzes the current technical bottlenecks and challenges in application, proposes corresponding countermeasures, and discusses future development directions, aiming to provide references and new insights for the intelligent screening and diagnosis of eye diseases.
Key words: eye disease; artificial intelligence; diagnosis; face; photo
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