眼科 ›› 2026, Vol. 35 ›› Issue (3): 177-186.doi: 10.13281/j.cnki.issn.1004-4469.2026.03.001.

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眼常规:系统性健康监测与预防医学检查新范式

王兴叶1,2   刘含若  徐捷 何海龙1   王宁利1   柯鑫2   金子兵1   

  1. 1首都医科大学附属北京同仁医院 北京同仁眼科中心 北京市眼科研究所,北京 100730;
    2依未科技(北京)有限公司视计算研究院,北京 100085
  • 收稿日期:2026-02-03 出版日期:2026-05-25 发布日期:2026-05-25
  • 通讯作者: 金子兵,Email:jinzb502@ccmu.edu.cn
  • 基金资助:
    国家自然科学基金青年A类项目(82125007);国家自然科学基金青年B类项目(82422018)

Ocular routine: a new paradigm for systemic health monitoring and preventive medical examination

Wang Xingye1,2, Liu Hanruo1, Xu Jie1, He Hailong1, Wang Ningli1, Ke Xin2, Jin Zibing1   

  1. 1 Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China; 2 Visual Computing Research Institute, EVision Technology (Beijing) Co. Ltd., Beijing 100085, China
  • Received:2026-02-03 Online:2026-05-25 Published:2026-05-25
  • Contact: Jin Zibing, Email: jinzb502@ccmu.edu.cn
  • Supported by:
    National Natural Science Foundation of China for Young Scholars, Class A (82125007), National Natural Science Foundation of China for Young Scholars, Class B (82422018).

摘要:   医学诊疗模式已从“以疾病为中心”向“以健康为中心”转变,早期筛查与预防成为应对慢性非传染性疾病负担的关键举措。视网膜作为人体唯一能无创、直接观测中枢神经系统与全身循环状态的窗口,其在全身健康评估中的价值日益凸显。本文系统梳理了基于人工智能(artificial intelligence, AI)技术量化视网膜影像特征的研究进展,阐述其在心血管疾病、神经退行性疾病、代谢性疾病、肾脏疾病以及血液系统疾病早期预警、风险分层和辅助诊断中的作用。基于此,本文创新性提出“眼常规”概念,将其定义为一套以AI驱动的多模态视网膜影像量化分析为核心,整合视力、眼压等基础检查进行标准化集成的系统性健康评估体系。同时,构建了“眼常规”体系架构,分析了其在人群筛查、多学科临床诊疗及健康管理等场景的实施路径与应用价值,并探讨了其面临的挑战及未来发展方向,旨在推动“眼常规”逐步发展为类似“血常规”的标准化基础检查项目,为夯实全民健康基础、实现精准预防医学提供创新性解决方案。

关键词:  , 眼与系统性疾病;眼常规;人工智能;定量分析;健康管理

Abstract:  Currently, the medical diagnosis and treatment paradigm has transitioned from “disease-centered” to “health-centered”, and early screening and disease prevention have emerged as crucial strategies for tackling the global burden of chronic non-communicable diseases. As the sole anatomical structure in the human body enabling non-invasive and direct observation of the central nervous system and the overall circulatory status, the retina's latent value in the assessment of overall health is increasingly prominent. This article systematically reviews the research progress in quantifying retinal image features using artificial intelligence (AI) technology and elaborates on its role in the early warning, risk stratification, and auxiliary diagnosis of cardiovascular diseases, neurodegenerative diseases, metabolic diseases, kidney diseases, and hematological diseases. Based on this, this article innovatively proposes the concept of "eye routine", which is defined as a systematic health assessment system that integrates AI-driven multi-modal retinal image quantification analysis as the core and standardizes the integration of basic examinations such as visual acuity and intraocular pressure. Meanwhile, a "routine eye examination" system architecture has been established. Its implementation paths and application values in scenarios such as population screening, multi-disciplinary clinical diagnosis and treatment, and health management have been analyzed. The challenges it faces and its future development directions have also been discussed. The aim is to promote the gradual development of the "routine eye examination" into a standardized basic examination project similar to the "routine blood test", providing innovative solutions for strengthening the foundation of national health and achieving precise preventive medicine.

Key words: Eye and systemic diseases, Eye routine, Artificial intelligence, Quantitative analysis, Health management