慢性肝病（chronic liver disease, CLD）是一种或多种损伤因素长期作用于肝脏导致的疾病总称，其影响范围广、患者人群基数大。病毒性肝炎、非酒精性脂肪性肝病和终末期肝病等慢性肝病会累及眼底，造成视网膜渗出、出血等病变；同时眼底结构改变，如脉络膜和视网膜不同层次厚度，也与慢性肝病严重程度相关。对慢性肝病患者进行眼底检查不仅用于防治相关的眼底并发症，也对肝病临床评估及监测具有潜在应用价值。文章综述不同病因、严重程度和药物治疗下的慢性肝病患者可能出现的眼底病变，以及眼底结构功能检查在慢性肝病患者中的临床应用进展，以比较不同眼底检查方法在慢性肝病患者临床实施过程中的特点及适用场景，并提示未来在慢性肝病患者中应用眼底检查的潜在新方向。

Chronic Liver Disease (CLD) is a collective term for diseases resulting from the long-term effects of one or more damaging factors on the liver. It has a broad impact and affects a large patient population. Viral hepatitis, non-alcoholic fatty liver disease, and end-stage liver disease can involve the ocular fundus, leading to retinal exudates and hemorrhages. Additionally, structural changes in the fundus, such as the thickness of the choroid and different retinal layers, are associated with the severity of chronic liver disease. Through fundus examinations in patients with chronic liver disease, not only can ocular complications related to liver disease be prevented and treated, but these examinations may also offer potential value in the clinical assessment and monitoring of liver disease. This article reviews the potential ocular fundus abnormalities in patients with chronic liver disease under different etiologies, severities, and drug treatments. It discusses the progress in the clinical application of fundus structure and function examinations in patients with chronic liver disease. It compares the characteristics and appropriate clinical scenarios of various fundus examination methods in these patients and suggests potential new directions for the future use of fundus examinations in chronic liver disease management.

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.

近年来随着医疗领域数字化、信息化建设的加速推进，人工智能的应用越来越广泛，在眼科医学方面尤为突出。婴幼儿处于视觉系统发育的关键时期，此时发生的眼病往往会造成不可逆的视功能损伤，带来沉重的家庭和社会负担。然而，由于婴幼儿群体的特殊性以及小儿眼科医生的短缺，开展大规模小儿眼病筛查工作十分困难。最新研究表明：人工智能在先天性白内障、先天性青光眼、斜视、早产儿视网膜病变以及视功能评估等领域已经得到相关应用，在多种婴幼儿眼病的早期筛查、诊断分期、治疗建议等方面都有令人瞩目的表现，有效解决了许多临床难点与痛点。但目前婴幼儿眼科人工智能仍然不如成年人眼科发展充分，亟须进一步的探索和研发。

In recent years, with the acceleration of digitalization and informatization in medical field, artificial intelligence (AI) is more and more widely applied, especially in ophthalmology. Infants are in the critical period of visual development, during which eye diseases can lead to irreversible visual impairment and bring heavy burden to family and society. Due to the particularity of infants and the shortage of pediatric ophthalmologists, it is challenging to carry out large-scale screening for eye diseases of infants. According to the latest studies, AI has been studied and applied in the fields of congenital cataract, congenital glaucoma, strabismus, amblyopia, retinopathy of prematurity, and evaluation of visual function, and it has achieved remarkable performance in the early screening, diagnosis stage and treatment suggestions, solving many clinical difficulties and pain points effectively. However, AI for infantile ophthalmology is not as developed as for adult ophthalmology, so it needs further exploration and development.

Blindness prevention has been an important national policy in China. Previous strategies, such as deploying experienced cataract surgeons to rural areas and assisting in building local ophthalmology centers, had successfully decreased the prevalence of visual impairment and blindness. However, new challenges arise with the aging population and the shift of the disease spectrum towards age-related eye diseases and myopia. With the constant technological boom, digital healthcare innovations in ophthalmology could immensely enhance screening and diagnosing capabilities. Artifcial intelligence (AI) and telemedicine have been proven valuable in clinical ophthalmology settings. Moreover, the integration of cutting-edge communication technology and AI in mobile clinics and remote surgeries is on the horizon, potentially revolutionizing blindness prevention and ophthalmic healthcare. The future of blindness prevention in China is poised to undergo signifcant transformation, driven by emerging challenges and new opportunities.

Blindness prevention has been an important national policy in China. Previous strategies, such as deploying experienced cataract surgeons to rural areas and assisting in building local ophthalmology centers, had successfully decreased the prevalence of visual impairment and blindness. However, new challenges arise with the aging population and the shift of the disease spectrum towards age-related eye diseases and myopia. With the constant technological boom, digital healthcare innovations in ophthalmology could immensely enhance screening and diagnosing capabilities. Artifcial intelligence (AI) and telemedicine have been proven valuable in clinical ophthalmology settings. Moreover, the integration of cutting-edge communication technology and AI in mobile clinics and remote surgeries is on the horizon, potentially revolutionizing blindness prevention and ophthalmic healthcare. The future of blindness prevention in China is poised to undergo signifcant transformation, driven by emerging challenges and new opportunities.

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.

随着智能手机覆盖率的增加与可用性的提升，实现智能健康管理的应用程序成为新兴研究热点。新一代智能手机可通过追踪步数，监测心率、睡眠，拍摄照片等方式进行健康分析，成为新的医学辅助工具。随着深度学习技术在图像处理领域的不断进展，基于医学影像的智能诊断已在多个学科全面开花,有望彻底改变医院传统的眼科疾病诊疗模式。眼科疾病的常规诊断往往依赖于各种形式的图像，如裂隙灯生物显微镜、眼底成像、光学相干断层扫描等。因此，眼科成为医学人工智能发展最快的领域之一。将眼科人工智能诊疗系统部署在智能手机上，有望提高疾病诊断效率和筛查覆盖率，改善医疗资源紧张的现状，具有极大的发展前景。综述的重点是基于深度学习和智能手机的眼病预防与远程诊疗的进展，以糖尿病性视网膜病变、青光眼、白内障3种疾病为例，讲述深度学习和智能手机在眼病管理方面的具体研究、应用和展望。

With the increasing coverage and availability of smart phones, the application of realizing intelligent health management has become an emerging research hotspot. The new generation of smart phones can perform health analysis by tracking the step numbers, monitoring heart rate and sleep quality, taking photos and other approaches, thereby becoming a new medical aid tool. With the continuous development of deep learning technology in the field of image processing, intelligent diagnosis based on medical imaging has blossomed in many disciplines, which is expected to completely change the traditional eye diseases diagnosis and treatment mode of hospitals. The conventional diagnosis of ophthalmic diseases often relies on various forms of images, such as slit lamp biological microscope, fundus imaging, optical coherence tomography, etc. As a result, ophthalmology has become one of the fastest growing areas of medical artificial intelligence (AI). The deployment of ophthalmological AI diagnosis and treatment system on smart phones is expected to improve the diagnostic efficiency and screening coverage to relieve the strain of medical resources, which has a great development prospect. This review focuses on the prevention and telemedicine progress of eye diseases based on deep learning and smart phones, taking diabetic retinopathy, glaucoma and cataract as examples to describe the specific research, application and prospect of deep learning and smart phones in the management of eye diseases.

近年来，使用人工智能(artificial intelligence，AI)技术对临床大数据及图像进行分析，对疾病做出智能诊断、预测并提出诊疗决策，AI正逐步成为辅助临床及科研的先进技术。生物样本库作为收集临床信息和样本供科研使用的平台，是临床与科研的桥梁，也是临床信息与科研数据的集成平台。影响生物样本库使用效率及合理共享的因素有信息化建设水平不均衡、获取的临床及检验信息不完全、各库之间信息不对称等。本文对AI和区块链技术在生物样本库建设中的具体应用场景进行探讨，展望大数据时代智能生物样本库信息化建设的核心方向。

In recent years, artificial intelligence (AI) technology has been applied to analyze clinical big data and images and then make intelligent diagnosis, prediction and treatment decisions. It is gradually becoming an advanced technology to assist clinical and scientific research. Biobank is a platform for collecting clinical information and samples for scientific research, serving as a bridge between clinical and scientific research. It is also an integrated platform of clinical information and scientific research data. However, there are some challenges. First, clinical and laboratory information obtained is incomplete. Additionally, the information among different databases is asymmetric, which seriously impedes the information sharing among different Biobanks. In this article, the specific application scenarios of AI technology and blockchain in the construction of a Biobank were discussed, aiming to pinpoint the core direction of the information construction of an intelligent Biobank in the era of big data.

目的：探讨上睑提肌缩短术和额肌肌瓣悬吊术后眼表改变和恢复的差异。

方法：对2007 年1 月至2007 年4 月在中山眼科中心住院的42例(62只眼)先天性上睑下垂患者，按手术方式和术后是否加用局部用药进行随机分组，观测各组术后2 d、5 d、7 d和2周患者泪液的分泌、泪膜破裂时间、结膜充血、角膜荧光染色、睑板腺功能、瞬目次数、上睑睫毛角度和眼睑闭合情况，并分析其观察结果的差异是否有统计学意义。

结果：3名患者(7.1 ％)因需要加用其它促角膜上皮生长的药物而退出本研究，其中1例(2.3 ％)因倒睫刺激角膜上皮水肿缺损需行手术调整，其余所有患者眼表检测项目的结果均显示不同程度地受到了手术影响，但是随着术后炎症的逐渐消退，这些受影响的眼表异常均会逐渐恢复正常。泪膜破裂时间、瞬目次数、眼睑闭合情况的影响在两种术式之间的差异有统计学意义，而在术后是否局部用药之间没有统计学差异；角膜荧光素染色在是否加用局部用药组之间有统计学差异，而不同术式之间没有统计学差异；泪液分泌量、结膜充血、睑板腺功能、睫毛角度则在所有组别之间均没有统计学差异。

结论：两种上睑下垂的矫正术均会引起患者眼表的改变，额肌肌瓣悬吊术对泪膜破裂时间、瞬目次数、眼睑闭合情况影响的程度较大，而局部用药只能改善角膜荧光素染色异常、对其它眼表因素影响不大。上睑睫毛角度异常是引起角膜损害最危险的因素。

Objective : To investigate the difference of ocular surface change and restoration after ex-ternal levator advancement and frontalis suspension.

Methods : Forty-two patients (62 eyes) with congenital ptosis hospitalized in ZhongshanOphthalmic Center from Jaruary to April in 2007 were randomly divided into four groups according to different surgery types and with or without post surgery ophthalmic medica-tion. Sehirmer test, tear film break-up time , conjunctiva congestion , cornea fluorescentpigmentation , tarsal gland function , winking frequency, angle of eyelash and eyelid clo-sure were all observed and statistically analyzed in all groups 2 days , 5 days , 7 days and 2 weeks after surgery.

Results : Except 3 patients needed advanced ophthalmic medicine, one of whom waswith corneal ulceration and needed another surgery, all the others were observed withocular surface items altered in varied degrees and gradually returned to normality as theinflammation caused by surgery recovered. Break-up time , winking frequency and eyelid closure were statistically diferent between the two types of surgery but not betweengroups with and without post surgery ophthalmic medication. Cornea fluorescent pigmen-tation was statistically different between groups with and without post surgery ophthalmicmedication but not between the two types of surgery. The other items did not have statis-tical difference in all groups.

Conclusion : The two types of surgery for ptosis correction could alter the ocular surface ,but frontalis suspension affect tear film break-up time , winking frequency and eyelid clo-sure much more than levator advancement. Ophthalmic medication after the surgerycould only ameliorate cornea fluorescent pigmentation but was not necessarily to restora-tion of normal ocular surface. Abnormality of eyelash angle was the most dangerous fac-tor to the corea injury.

      调节是人眼非常重要的功能，通过调节能随时改变人眼屈光系统的光学参数，与眼屈光不正及老视都有着密切的关系。测量眼调节力的常用方法分为主观测量法和客观测量法。主观测量法以移近移远法、负镜片法为代表。客观测量法以动态视网膜检影法和自动屈光仪法为代表。本文就调节力测量方法、测量准确度和调节力的最新研究进展进行综述，为眼科临床研究和应用提供选择依据。

Accommodation is an important function of the human eye, which can change the parameters of ocular refractive system and also has a strong correlation with the development of myopia and presbyopia. Several subjective measurements have been applied in accommodation assessment such as push-up test, push-down test and minus-lens procedures. It can be measured objectively by measuring the change in refraction of the eye with dynamic retinoscopy or autorefractor. This article reviews the application of measurement of accommodative amplitude and research progress in accommodation, providing clinical information for further studies．