近年来随着人口老龄化的发展、人群用眼方式的改变，现有的眼科医疗资源正越来越难以满足日渐增长的医疗需求，亟需新型的诊疗模式予以补足。眼科人工智能作为眼科领域的新兴元素，在眼病的筛查诊断中发展迅速，主要表现为“眼部图像数据+人工智能”的模式。近年来，随着该模式在白内障、青光眼、糖尿病性视网膜病变(diabetic retinopathy，DR)等常见病中研究的深入，相关技术日渐成熟，表现出了较大的应用优势与应用前景，部分技术甚至成功转化并被逐渐应用于临床。眼科诊疗向智慧医学模式的过渡，有望缓解日益增长的医疗需求与紧缺的医疗资源之间的矛盾，从而提高整体的医疗服务水平。
The development of population aging and changes in the way people use their eyes over the recent years have increasingly challenged the existing ophthalmic medical resources to meet the growing medical needs, thus urgently calling for a novel diagnostic and treatment mode. Despite its status as an emerging sector in ophthalmology, ophthalmic artificial intelligence has developed rapidly in the screening and diagnosis of eye diseases, as can be seen in practices adopting the “eye imaging data + AI” mode. In recent years, with the intensified research on this mode with respect to common diseases such as cataract, glaucoma and diabetic retinopathy, relevant technologies have grown increasingly mature, presenting undeniable application superiority and prospects. Some of the relevant technical achievements have also been successfully transformed for practical usage, and are gradually being applied to clinical practices. Ophthalmic diagnosis and treatment are transitioning toward the era of intelligent medical services, which are expected to reduce the contradictions between the growing medical needs and the shortage of medical resources, as well as ultimately improve the overall experience of medical services.
阿尔茨海默病(Alzheimer’s disease，AD)是发生于老年期或老年前期的中枢神经系统退行性病变，以进行性认知功能障碍为特征。随着社会老龄化加剧，AD已成为全球公共卫生问题，亟需研发更敏感、便捷和经济的筛查技术进行早期防控。眼球运动与认知功能密切相关，且眼球运动检查有非侵入性、成本低、检查时间短等优点。研究眼球运动异常和认知功能障碍之间的相关性，有助于研发更简便易操作的认知功能障碍筛查工具。随着人工智能技术的发展，机器学习算法强大的特征提取和计算能力对处理眼球运动检查结果有显著优势。本文对既往AD患者与眼球运动异常之间的相关性研究进行综述，并对机器学习算法模型辅助下，基于眼球运动异常模式进行认知功能障碍早期筛查技术开发的研究前景予以展望。
Alzheimer’s disease (AD) is a degenerative disease of the central nervous system that occurs in old age or early old age. It is characterized by progressive cognitive dysfunction. With the world population aging, AD has become a global public health problem. The development of a more sensitive, convenient, and economic screening technology for AD is urgently needed. The eye movement function is closely related to cognitive function. Moreover, eye movement examination has advantages including non-invasiveness, low cost, and short examination time. Researches on the correlation between abnormal eye movement and cognitive dysfunction can help to develop a simple and easy-to-use screening tool for cognitive dysfunction. With the development of artificial intelligence technology, the dominant feature extraction and computing capabilities of machine learning algorithms have a significant advantage in processing eye movement inspection results. This article reviews the correlation between AD and eye movement abnormalities aiming to provide the research prospects of early screening technology development for cognitive dysfunction based on abnormal eye movement with the application of machine learning models.
目的：依托最新的第5代移动通信技术(5th generation wireless systems，5G)，构建基于眼底图片的5G医疗眼科远程诊断平台，促进医疗资源上下贯通，提升基层服务能力及医疗服务体系整体效能。方法：基于5G时代医院的信息化发展战略，在海南省卫生健康委员会的资助与指导下，中山大学中山眼科中心海南眼科医院与中国联通通信集团海南有限公司等进行跨行业、多学科的技术力量研究开发，构建5G条件下的平台建设模块和技术路线，确定远程眼科诊断流程，并在海南省内多地区应用。结果：远程诊断平台运行良好。2020年12月至2021年11月，本研究共在海南省17个地区的186个卫生院中开展，共收集1561例患者眼底病图片数据，筛查阳性例数为185例，检出眼底病总阳性率为11.9%。其中有42例需要转诊治疗，转诊率为23%；143例不需要转诊治疗，非转诊率为77%。在1561例眼底图像中，采集异常的眼底图像有490例。排除490例异常眼底图像后，辅助诊断系统与人工诊断结果有1 002张眼底图像诊断相同，69张眼底图像诊断不同，其辅助诊断系统准确率为93.3%。结论：5G移动通信与远程医学影像结合，运用互联网科技催生新型医疗生产力，提高卫生经济的质量和效率，是医疗领域探索5G应用场景的一项应用典范。
Objective: Relying on the latest 5th generation wireless systems (5G), a remote primary ophthalmology care diagnosis platform based on fundus images was constructed in order to promote the connectivity of medical resources and improve the primary health service capabilities and the overall effectiveness of the medical service system. Methods: Based on the 5G informatization development strategy of hospitals, and under the funding and guidance of the Hainan Provincial Health Commission, the Hainan Eye Hospital of Zhongshan Ophthalmic Center and China Unicom Communications Group Hainan Co., Ltd. conducted a cross-industry, multi-disciplinary technical research. To build platform construction modules and technical routes under 5G networks, present the remote ophthalmological diagnosis process, and apply it in many regions in Hainan Province. Results: The performance of the remote diagnosis platform is well. From December 2020 to November 2021, this study was carried out in 186 health centers in 17 regions of Hainan Province. A total of 1 561 patients with fundus disease image data were collected. The number of positive screening fundus disease cases was 185. The total positive rate was 11.9%. Among them, 42 cases required referral for treatment, with a referral rate of 23%, and 143 cases did not require referral for treatment, with a non-referral rate of 77%. Among 1 561 cases of fundus images, 490 fundus images were excluded due to abnormal quality. Compared the results of the diagnosis platform system with manual diagnosis, 1 002 fundus images were identical, and 69 fundus images were different in diagnosis. The accuracy of the auxiliary diagnosis system was 93.3%. Conclusions: The collaboration of 5G mobile communication and telemedicine imaging, combined with internet technology to promote new medical productivity, improve quality and efficiency of the health economy. This study is an application model for exploring 5G application scenarios in the medical field.
全身疾病通过一定途径累及眼球，产生眼部病变，这些眼部病变的严重程度与全身疾病的进展密切相关。人工智能(artificial intelligence，AI)通过识别眼部病变，可以实现对全身疾病的评估，从而实现全身疾病早期诊断。检测巩膜黄染程度可评估黄疸；检测眼球后动脉血流动力学可评估肝硬化；检测视盘水肿，黄斑变性可评估慢性肾病(chronic kidney disease，CKD)进展；检测眼底血管损伤可评估糖尿病、高血压、动脉粥样硬化。临床医生可以通过眼部影像评估全身疾病的风险，其准确度依赖于临床医生的经验水平，而AI识别眼部病变评估全身疾病的准确度可与临床医生相媲美，在联合多种检测指标后，AI模型的特异性与敏感度均可得到显著提升，因此，充分利用AI可实现全身疾病的早诊早治。
Systemic diseases affect eyeballs through certain ways, resulting in eye diseases; The severity of eye diseases is closely related to the progress of systemic diseases. By identifying eye diseases, artificial intelligence (AI) can assess systemic diseases, so as to make early diagnosis of systemic diseases. For example, detection of the degree of icteric sclera can be used to assess jaundice. Detection of the hemodynamics of posterior eyeball can be used to evaluate cirrhosis. Detection of optic disc edema and macular degeneration can be used to evaluate the progress of chronic kidney disease (CKD). Detection of ocular fundus vascular injury can be used to assess diabetes, hypertension and atherosclerosis. Clinicians can estimate the risk of systemic diseases through eye images, and its accuracy depends on the experience level of clinicians, while the accuracy of AI in identifying eye diseases and evaluating systemic diseases can be comparable to clinicians. After combining various detection indexes, the specificity and sensitivity of AI model can be significantly improved, so early diagnosis and early treatment of systemic diseases can be realized by making full use of AI.
随着人工智能(artificial intelligence,AI)技术的快速发展，其在医疗领域的应用正带来革命性的变化。白内障作为全球范围内最常见的可逆性视力障碍之一，在管理和治疗方面依然存在着医疗资源不足、诊断精度低、转诊效率低等诸多实际问题。因此，利用AI技术强大的计算分析和智能决策能力，优化传统医疗实践方式，对于保障人们的视觉健康至关重要。该文探讨AI技术在推动白内障分级诊疗新模式方面的应用，包括白内障图像自动分析与识别、远程医疗和转诊支持等，这些应用能够为白内障患者、社会以及政府带来多方面的显著益处和重要影响，有助于提高白内障诊断和治疗效率，缓解医疗资源不均衡问题，优化医疗资源的配置和管理，推动社会健康进步。然而，AI技术的实际应用也面临风险和挑战，应当充分重视和保护患者数据隐私和安全，建立严格的监管和监督机制，并持续加强技术创新，全面评估AI算法的鲁棒性、公平性和可解释性，以进一步提高AI系统的准确度和可信度。
With the rapid development of artificial intelligence (AI) technology, its application in the field of healthcare is bringing revolutionary changes. Cataracts, as one of the most common reversible visual impairments worldwide, still face many practical issues in terms of limited medical resources, low diagnostic accuracy, and low referral efficiency. Therefore, it is crucial to utilize AI technology's powerful computational analysis and intelligent decision-making capabilities to optimize traditional medical practices and safeguard people's visual health.This article investigates the applications of AI technology on a new model of hierarchic diagnosis and treatment for cataracts, including automatic analysis and recognition of cataract images, remote healthcare, and referral support. These applications can bring significant benefits and important impacts to cataract patients, society, and governments. They can help improve the efficiency of cataract diagnosis and treatment, alleviate the imbalance of medical resources, optimize the allocation and management of healthcare resources, and promote societal health progress.However, the practical application of AI technology also faces risks and challenges. It is important to fully prioritize and protect patients' data privacy and security by establishing strict regulatory and oversight mechanisms. Additionally, continuous efforts should be made to enhance technological innovation and comprehensively evaluate the robustness, fairness, and interpretability of AI algorithms to further improve the accuracy and trustworthiness of AI systems.
人工智能(artificial intelligence，AI)在眼科领域的应用不断深入、拓展，目前在糖尿病性视网膜病变、白内障、青光眼以及早产儿视网膜病变在内的多种常见眼病的诊疗中逐渐成为研究热点。AI使医疗资源短缺、诊断标准缺乏、诊疗技术水平低下的现状得到改善，为白内障的诊疗开辟了一条“新赛道”。本文旨在综述AI在白内障诊疗中的应用现状、进展及局限性，为AI在白内障领域的进一步开发、应用及推广提供更多信息。
Artificial intelligence (AI) has been widely applied and promoted in ophthalmology, and has gradually become a research hotspot in the diagnosis and treatment of many common ophthalmopathies, including diabetic retinopathy, cataract, glaucoma, and retinopathy of prematurity. AI improves the shortage of medical care, the lack of diagnostic criteria and the low level of diagnosis and treatment technology, and explores a “new race track” for cataract diagnosis and treatment. The purpose of this article is to review the application status, progress and limitations of AI in the diagnosis and treatment of cataract, aiming to provide more information for further development, application and promotion of AI in the field of cataract.
原发性干燥综合征(primary Sj?gren’s syndrome，SS)是一种主要累及外分泌腺体的自身免疫性疾病，患者通常因为严重的干眼症状首先就诊于眼科，大多数临床医师对原发性干燥综合征相关性干眼(Sj?gren’s syndrome dry eye disease，SS-DED)认识不足，可能导致漏诊和误诊。侵入性极小的客观检查及生物标志物的发展，将有助于发现SS-DED的真面目，并可能从新的角度阐释其发病机制，为其诊断、分类及治疗提供新的思路。SS-DED的治疗没有特效的药物，大多数患者需接受多种方法的治疗，以了解哪些方法最有效。
Primary Sj?gren’s syndrome is an autoimmune disease that mainly affects exocrine glands. Patients usually refer to ophthalmologists because of severe dry eye symptoms. Most clinicians have insufficient knowledge with dry eye disease associated with primary Sj?gren’s syndrome probably leading to misdiagnosis or missing the diagnosis.The diagnosis of Sj?gren’s syndrome dry eye disease (SS-DED) is difficult, but the extremely invasive objective examination and the development of biomarkers will help to understand this disease and explain its pathogenesis from a new perspective. There is no specific treatment for the SS-DED, and most patients should receive multiple treatments to select the optimal treatment.
目的：探讨眼科住院医师规范化培训中睑板腺囊肿诊疗的培训效果及存在的问题，以期改进培训方式。方法：以2020年4月在中山大学中山眼科中心培训的154名学员为对象，进行问卷调查，采用SPSS 20.0统计学软件进行数据分析。结果：共76名专业型硕士(专硕)、78名住院医师培训(住培)学员完成了问卷调查。专硕具有睑板腺囊肿诊断、保守治疗及手术主刀经验的比例分别为40.8%、11.8%、7.9%；住培则显著高于前者，分别为79.5%(P<0.001)、60.3%(P<0.001)和21.8%(P=0.016)。对于关键诊疗环节的判断，90.8%的专硕选择了临床诊断(P=0.007)，94.9%的住培则选择治疗方案(P<0.001)。去除囊壁、术中意外与破溃皮肤的处理是专硕难以掌握的手术步骤(P<0.001)；而住培仅为去除囊壁(P<0.001)。结论：睑板腺囊肿诊疗水平在眼科住院医师规范化培训中亟待提高，并根据各类型学员的临床能力和认知差异，进行分级分类培训。
Objective: To explore the teaching effect of diagnosis and treatment on chalazion in the standardized training of ophthalmology residents and its existing problems, in order to improve the quality of the training systems. Methods: A self-designed questionnaire survey was conducted with 154 ophthalmology residents in Zhongshan Ophthalmic Center in April 2020, and the investigative data was analyzed using SPSS 20.0. Results: Totally 76 medical postgraduates and 78 ophthalmology residents completed the questionnaire survey. The proportions of medical postgraduates who had individual experience on diagnosis, conservative and surgical treatment of chalazion were 40.8%, 11.8%, and 7.9%. Compared to the former, ophthalmology residents had significantly higher proportion, with 79.5% (P<0.001), 60.3% (P<0.001), and 21.8% (P=0.016), respectively. For judging the important aspect of diagnosis and treatment process, the medical postgraduates chose the clinical diagnosis (90.8%) (P=0.007), while the ophthalmology residents paid more attention on treatment options (94.9%) (P<0.001). In the surgical procedures, removal of cyst wall, management of intraoperative accidents and skin ulcers are all their difficult skills to master for medical postgraduates (P<0.001), while only removal of cyst wall for residents (P<0.001). Conclusion: The training level of diagnosis and treatment of chalazion still needs to be improved in the standardized training of ophthalmology residents. The training should be carried out according to the clinical competence and cognition differences of various types of students.
眼附属器淋巴组织增生性疾病作为一类疾病的总称，包括了良性淋巴组织增生、非典型性淋巴组织增生、IgG4相关眼病以及多种恶性淋巴瘤在内的数十种疾病类型。临床诊断此类疾病应将患者眼部体征、影像学检查与病理学检查紧密结合。随着免疫表型及分子病理等检测技术的进步，此类疾病之间的鉴别诊断正逐渐清晰。本文就眼附属器淋巴组织增生性疾病进行系统性描述，并重点探讨该类疾病的病理鉴别诊断。
Ocular adnexal lymphoproliferative disease, as a general term, contains reactive lymphoid hyperplasia, atypical lymphoid hyperplasia, IgG4 related ocular disease and malignant lymphoma. The clinical diagnosis of this kind of disease should integrate patient’s symptoms, imaging features and pathology characteristics. Development of immunophenotyping, molecular pathology and other detection technology will help with the differential diagnosis of ocular adnexal lymphoproliferative disease. This article is going to discuss the etiology, epidemiology,diagnosis and treatment of ocular adnexal lymphoproliferative disease, with a focus on the clinicopathological differential diagnosis of such disease.
目的：借助于人工智能(artificial intelligence,AI)眼底筛查远程接转诊系统，探索“患者-社区-医院”远程筛查模式，推进眼科分级诊疗和双向转诊实施，为地市级医疗机构开展眼底疾病人工智能筛查工作提供一定的经验借鉴。方法：通过AI辅助远程筛查基层医疗机构的4886例患者，完成眼科检查并经AI初判、人工复核形成眼底诊断结论。通过医联体和专科联盟模式，对基层医疗机构的4886例患者的AI诊断系统结果和上级医师审核结果进行对照分析，分析AI诊断系统在眼科常见病种筛查中的推广应用的可信度和可行性。结果：AI检出DR的灵敏度为94.70%，特异度96.06%；DME的灵敏度96.43%，特异度96.55%；AMD的灵敏度77.55%，特异度95.74%；同时，其在病理性近视、白内障、青光眼等常见病种眼底筛查中也有一定作用。结论：AI辅助远程筛查系统对于绝大多数眼底疾病有较高的敏感性和特异性，适用于眼底疾病的筛查工作，利于基层医院或社区医院对于眼底疾病的初步诊断，落实眼科分级诊疗，有借鉴推广意义。
Objective: With the help of artificial intelligence (AI) based fundus screening remote referral telemedicine system,it enables us to explore the remote screening mode of patient-community-hospital, and promote the two-way referral and ophthalmic graded diagnosis. This investigation provides certain practice experiences for prefecture-level medical institutions to carry out AI screening for fundus diseases. Methods: Ophthalmologic examination was performed on 4,886 patients in primary medical institutions through AI-aided remote screening, and the final fundus diagnosis conclusion was formed after AI preliminary judgment and manual review. Through the Medical Consortium and specialty alliance model, the results of the AI diagnosis system and the audit results of superior physicians for 4 886 patients in primary care institutions were compared and analyzed, and the credibility and feasibility of the AI diagnosis system application in the screening of common ophthalmic diseases were discussed. Results: The sensitivity and specificity of AI detection of diabetic retinopathy were 94.70% and 96.06%, respectively. In the diabetic macular edema classification, the sensitivity and specificity were 96.43% and 96.55%, respectively. In the age-related macular degeneration classification, the sensitivity and specificity were 77.55% and 95.74%, respectively. Meanwhile, it also plays a role in screening common fundus diseases such as pathological myopia, cataract and glaucoma. Conclusion: The AI-aided remote screening system has high sensitivity and specificity for most of fundus diseases, indicating it is promising for fundus diseases screening in primary medical institutions. It is conducive for primary hospitals or community hospitals to carry out the initial diagnosis of fundus diseases, as well as the implementation of graded diagnosis and treatment of ophthalmology, which has reference and promotion significance.
