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.

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.

随着微创玻璃体切除术(pars plana vitrectomy，PPV)的广泛开展和手术技术的提高，患者对手术后视觉质量的要求越来越高。白内障是PPV术后最常见并发症，而具有玻璃体切除史的白内障患者屈光变异大，预测难度高。本文综述了生物测量误差、人工晶状体屈光力计算公式选择以及有效晶状体位置预测等影响有玻璃体切除手术史的白内障患者术后屈光误差的主要因素，旨在为降低这一类特殊人群白内障术后屈光误差提供参考。

With the widespread application of minimally invasive vitrectomy and the improvement of surgical techniques, the demands of patients for better postoperative visual quality are increasing. Cataract is the most common complication after vitrectomy, whereas the refractive outcomes of cataract patients with prior vitrectomy are viable and difficult to predict. In this paper, the main factors affecting postoperative refractive error of cataract patients with a history of vitrectomy, such as biometric error, selection of intraocular lens calculation formulas and prediction of effective lens position, were reviewed in order to provide reference for reducing postoperative refractive error of this special group of cataract patients.

目的：在硅油取出联合白内障手术患者中，使用扫频源光学相干断层扫描生物测量仪OA-2000进行生物测量，比较10种人工晶状体(IOL)屈光力计算公式的准确性。方法：回顾性分析2021年3月—7月于中山大学中山眼科中心接受硅油取出联合白内障手术的患者共62例(62眼)，所有患者均使用扫频源光学相干断层扫描生物测量仪OA-2000进行生物学参数测量。计算并比较新公式[Barrett Universal II (BUII)、Emmetropia Verifying Optical(EVO) 2.0、Hill-Radial Basis Function (Hill-RBF) 3.0、Hoffer QST、Kane、Pearl-DGS]及传统公式(Haigis、Hoffer Q、Holladay 1、SRK/T)的预测准确性，主要评价指标为绝对预测误差中位数(MedAE)及平均绝对预测误差(MAE)。按眼轴长度≤23 mm(组1)，>23 mm且≤26 mm(组2)与>26 mm(组3)进行亚组分析。结果：6个新公式、Haigis、SRK/T公式均出现近视漂移(-0.47 ~-0.27 D，P<0.05)，而HofferQ及Holladay 1公式无系统误差(P>0.05)。Kane公式的MedAE(0.55 D)及MAE(0.81 D)最小，但公式间比较差异无统计学意义(P>0.05)。组1中所有公式均出现近视漂移(-1.46~ -1.25 D，P<0.05)，而其他亚组比较差异无统计学意义(-0.32 ~ 0.41 D，P>0.05)。在组1中，Pearl-DGS公式的MedAE(0.97 D)及MAE(1.26 D)最小，且优于Hill-RBF 3.0(P=0.01)及SRK/T公式(P=0.02)；组2中，Kane公式具有最小的MedAE(0.44 D)及MAE(0.66 D)；组3各个公式屈光预测准确性比较差异无统计学意义(P>0.05)。结论：在使用OA-2000进行术前生物测量时，Kane公式在接受硅油取出联合白内障手术患者中的预测准确性较高；而眼轴长度≤23 mm时，Pearl-DGS公式可能更为准确。

Objective: To compare the accuracy of 10 intraocular lens (IOL) power calculation formulas in patients undergoing combined silicone oil removal and cataract surgery, biometry is performed using the swept-source optical coherence tomography biometer OA-2000. Methods: A retrospective analysis. A total of 62 patients (62 eyes) who underwent combined silicone oil removal and cataract surgery in Zhongshan Ophthalmic Center, Sun Yat-sen University from March to July in 2021 were enrolled. Preoperative biometry was performed by OA-2000 in all patients. New-generation formulas (Barrett Universal II [BUII], Emmetropia Verifying Optical [EVO] 2.0, Hill-Radial Basis Function [Hill-RBF] 3.0, Hoffer QST, Kane and Pearl-DGS) and traditional formulas (Haigis, Hoffer Q, Holladay 1 and SRK/T) were evaluated. The median absolute prediction error (MedAE) and mean absolute prediction error (MAE) were the main parameters used to assess accuracy. Subgroup analyses were performed based on the axial length of 23 mm and 26 mm. Results: Six new-generation formulas, Haigis, and SRK/T showed myopic shift (-0.47 ~ -0.27 D, P<0.05), while no systematic bias was found in Hoffer Q and Holladay 1 displayed (P>0.05). The smallest MedAE (0.55 D) and MAE (0.81 D) were found in Kane formula, but there was no statistically significant difference compared with other formulas (P>0.05). The myopic shift (-1.46 ~ -1.25 D, P<0.05) in eyes shorter than 23 mm were found in all formulas, while there was no significant systematic bias (-0.32 ~ 0.41 D, P>0.05) in other subgroups. In axial length shorter than 23 mm, the Pearl-DGS formula stated the smallest MedAE (0.97 D) and MAE (1.26 D), and was significantly more accurate than Hill-RBF 3.0 (P=0.01) and SRK/T (P=0.02). In eyes with an axial length between 23 mm and 26 mm, the Kane formula had the lowest MedAE (0.44 D) and MAE (0.66 D). No significant difference was found in eyes longer than 26 mm. Conclusion: The Kane formula showed the highest accuracy in patients undergoing combined silicone oil removal and cataract surgery measured by OA-2000, whereas the Pearl-DGS formula could be more accurate in eyes with an axial length shorter than 23 mm.

准分子激光原位角膜磨镶术(laser-assisted in situ keratomileusis,LASIK)是矫正屈光不正的重要角膜屈光手术方式之一。经过准分子激光切削的角膜，生物测量数据发生改变。对于此类患者，通过常规测量获得的参数数据以及使用常规计算公式确定的IOL屈光度将变得不再准确，由此将会导致术后较大的屈光误差，进而影响患者的视觉质量。本文报道一例46岁的男性白内障患者。该患者既往双眼屈光不正，曾接受过LASIK手术治疗。白内障术前角膜地形图检查发现该患者双眼存在角膜偏心切削，这为IOL屈光度的确定带来困难。手术医生通过角膜地形图判断角膜切削的居中性，在特定区域内选择角膜曲率K值，并采用Barrett True K公式计算出IOL屈光度。白内障术后患眼屈光误差相对较小，视力提高，视觉质量改善。

Laser-assisted in situ keratomileusis (LASIK) is a crucial corneal refractive surgery for correcting refractive errors. The cornea, after undergoing excimer laser ablation, undergoes changes in biometric measurements. For such patients, conventional measurements and IOL power calculations based on standard formulas may no longer be accurate, leading  to significant postoperative refractive errors and subsequently impacting the patient's visual quality. This article presents a case of a 46-year-old male cataract patient who had a history of refractive errors in both eyes and had previously undergone LASIK surgery. Preoperative corneal topography revealed corneal eccentric ablation in both eyes, posing challenges in determining IOL power. The surgeon assessed the centration of corneal ablation using corneal topography, selected the keratometry value (K value) within specific corneal regions, and calculated the IOL power using the Barrett True K formula. Postoperatively, the cataract patient experienced relatively minor refractive errors, leading to improved vision and enhanced visual quality.

近年来，眼部电流刺激(electrical stimulation,ES)在不同方向的研究中逐渐揭示了其在多种视网膜疾病中的潜在治疗价值。其中，经角膜电刺激(transcorneal electrical stimulation,TES)作为一种非侵入性的治疗方法，能对视网膜、视神经、眼底血管及其相关结构产生积极的影响。TES能够改善视力，在保护感光细胞和减缓疾病进展方面显示出积极效果，提高患者的生存质量，还能够在不损伤眼球的情况下调节大脑中的神经元活动，为视网膜疾病的治疗提供一种新的选择。该文对近年来TES在视网膜色素变性(retinitis pigmentosa,RP)、年龄相关性黄斑变性(age-related macular degeneration,AMD)、视网膜血管病、青光眼以及视神经病变等疾病中的应用研究进行了综述。研究发现，TES治疗是一种安全且无需手术的辅助治疗工具，具有广泛的应用前景。该文旨在为临床医师提供一个全面的TES研究概述，并深入探讨其在眼科学领域的潜在应用价值。然而，TES治疗的具体机制仍需进一步探讨，以便更好地应用于临床实践。同时，未来研究还应关注TES与其他治疗方法相结合的效果，以期为患者提供更多有效的治疗选择。

In recent years, electrical stimulation of the eye (ES) has gradually revealed its potential therapeutic value in a variety of retinal diseasesin different directions. Among them, transcorneal electrical stimulation (TES), as a non-invasive treatment, can have a positive effect on the retina, optic nerve, fundus vessels and related structures. TES can improve vision, show positive effects in protecting photoreceptor cells and slowing disease progression, improve the quality of life of patients, and can regulate neuronal activity in the brain without damaging the eyeball, providing a new option for the treatment of retinal diseases. The research on the application on TES on retinitis pigementosa (RP), age-related macular degeneration (AMD), retinal angiopathy, glaucoma and optic neuropathy are reviewed in this article. It is found in the study that TES therapy is a safe and surgery-free adjuvant therapy tool, and has a wide application prospect. The purpose of this article is to provide clinicians with a comprehensive overview of TES research,and to explore its potential application value in the field of ophthalmology. However, the specific mechanism of TES therapy still needs to be further explored in order to better apply in clinical practice. At the same time, future studies should also focus on the effect of combining TES with other treatment methods, in order to provide more effective treatment options for patients.

目的：建立和验证一个涉及多级临床场景的白内障协作通用的人工智能(artificial intelligence,AI)管理平台，探索基于AI的医疗转诊模式，以提高协作效率和资源覆盖率。方法：训练和验证的数据集来自中国AI医学联盟，涵盖多级医疗机构和采集模式。使用三步策略对数据集进行标记: 1)识别采集模式；2)白内障诊断包括正常晶体眼、白内障眼或白内障术后眼；3)从病因和严重程度检测需转诊的白内障患者。此外，将白内障AI系统与真实世界中的居家自我监测、初级医疗保健机构和专科医院等多级转诊模式相结合。结果：通用AI平台和多级协作模式在三步任务中表现出可靠的诊断性能: 1)识别采集模式的受试者操作特征(receiver operating characteristic curve,ROC)曲线下面积(area under the curve,AUC)为99.28%~99.71%)；2)白内障诊断对正常晶体眼、白内障或术后眼，在散瞳-裂隙灯模式下的AUC分别为99.82%、99.96%和99.93%，其他采集模式的AUC均 > 99%；3)需转诊白内障的检测(在所有测试中AUC >91%)。在真实世界的三级转诊模式中，该系统建议30.3%的人转诊，与传统模式相比，眼科医生与人群服务比率大幅提高了10.2倍。结论：通用AI平台和多级协作模式显示了准确的白内障诊断性能和有效的白内障转诊服务。建议AI的医疗转诊模式扩展应用到其他常见疾病和资源密集型情景当中。

Objective: To establish and validate a universal artificial intelligence (AI) platform for collaborative management of cataracts involving multilevel clinical scenarios and explored an AI-based medical referral pattern to improve collaborative efficiency and resource coverage. Methods: The training and validation datasets were derived from the Chinese Medical Alliance for Artificial Intelligence, covering multilevel healthcare facilities and capture modes. The datasets were labelled using a three step strategy: (1)capture mode recognition; (2) cataract diagnosis as a normal lens, cataract or a postoperative eye and (3) detection of referable cataracts with respect to aetiology and severity. Moreover, we integrated the cataract AI agent with a real-world multilevel referral pattern involving self-monitoring at home, primary healthcare and specialised hospital services. Results: The universal AI platform and multilevel collaborative pattern showed robust diagnostic performance in three-step tasks: (1) capture mode recognition (area under the curve (AUC) 99.28%–99.71%), (2) cataract diagnosis (normal lens, cataract or postoperative eye with AUCs of 99.82%, 99.96% and 99.93% for mydriatic-slit lamp mode and AUCs >99% for other capture modes) and (3)detection of referable cataracts (AUCs >91% in all tests). In the real-world tertiary referral pattern, the agent suggested 30.3%  of people be ’referred’, substantially increasing the ophthalmologist-to-population service ratio by 10.2-fold compared with the traditional pattern. Conclusions: The universal AI platform and multilevel collaborative pattern showed robust diagnostic performance and effective service for cataracts. The context of our AI-based medical referral pattern will be extended to other common disease conditions and resource-intensive situations.

患者，男性，1岁9个月。以“发现右眼上、下眼睑肿物25 d”首诊于眼科，要求切除，但经影像学及病理学检查，诊断为多发性朗格汉斯细胞组织细胞增生症，且全身骨骼多处出现溶骨性改变，不符合切除指征。给予多次全身化学治疗后眼部肿物明显变小。该例诊治提醒眼科医生，眼部肿物可由全身系统性疾病引起，不可盲目切除，必要时做进一步检查。术中切除物均建议行病理活组织检查，以免延误治疗。

patient, male, 1year and 9months old, was first diagnosed as “eye tumor” in the ophthalmology department and requested for excision. But it was diagnosed as multiple Langerhans cell histiocytosis (LCH) through imaging and pathological examination ultimately.Bone lytic changes appeared in many parts of the whole body, which did not meet the indication of excision.The tumor was smaller after systemic chemotherapy. The diagnosis and treatment of this case suggests ophthalmologists that eye tumors can be caused by caused by systemic diseases, systemic diseases. During operation, it is recommended to perform pathological biopsy to avoid treatment delay.

甲状腺相关眼病(thyroid-associated ophthalmopathy,TAO)，又称Graves眼病，是与甲状腺疾病密切相关的一种器官特异性自身免疫性疾病。眼球突出是TAO的主要临床表现之一，也是临床上多数患者就诊的原因。眼球突出一方面会影响美观，另一方面可因眼睑闭合不全导致暴露性角膜炎或因眼眶压力增大导致压迫性视神经病变。眼眶减压术用于重度TAO已有过百年历史，从最早经外眦皮肤切开的传统外部切口入路进行骨性眼眶减压及脂肪减压到内镜下经鼻入路眼眶减压术，其安全性和有效性均已得到肯定。术后复视是眼眶减压术常见的并发症。近年来，随着眼眶减压术的发展，其越来越多地用于美容目的以矫正眼球突出。然而术后的新发复视仍然是困扰众多相关眼科医疗工作者的难题。近年来，多项研究对术后新发复视的相关因素进行了探讨，并由此对眼眶减压术进行改良，在对术后新发复视的减少方面取得不同程度的进展。该文对眼眶减压术后新发复视的研究进展进行综述，旨在促进专科医生更精准地开展TAO的手术，进而提高手术患者术后的生活质量及手术满意度。

Thyroid-associated ophthalmopathy (TAO), known as Graves’orbitopathy, is an organ specific autoimmune disease closely related to thyroid diseases. Exophthalmos is one of the main clinical manifestations of thyroid related ophthalmopathy and is also the reason for most patients seeking medical atention in clinical practice.Eyeball protrusion can afect aesthetics on the one hand, and on the other hand, it can lead to exposed keratitis due to incomplete closure of the eyelids or compressive optic neuropathy due to increased orbital pressure.Orbital decompression has been used to treat severe TAO that threatens vision for over 100 years, and its safety and efectiveness have been confrmed.However, postoperative new diplopia remains a challenge for many ophthalmic medical workers.In recent years, many studies have explored the relevant factors of postoperative new diplopia, and improved the surgery, achieving varying degrees of progress in reducing postoperative new diplopia.Tis article reviews the research progress of new diplopia afer orbital decompression, aiming to promote more accurate surgery for thyroid related eye diseases by specialized doctors.

Congenital cataract (CC) is one of the most common causes of pediatric visual impairment.As our understanding of CC's etiology, clinical manifestations, and pathogenic genes deepens,various CC categorization systems based on diferent classifcation criteria have been proposed.Regrettably, the application of the CC category in clinical practice and scientifc research is limited. It is challenging to obtain preciseinformation that could guide the timely treatment decision-making for pediatric cataract patients or predict their prognosis from a specificCC classification. This review aims to discuss the statusquo of CC categorization systems and the potential directions for future research in this field, focusingon categorization principles and scientificapplication in clinical practice.Additionally, it aims to propose the potential directions for future research in this domain.

Congenital cataract (CC) is one of the most common causes of pediatric visual impairment.As our understanding of CC's etiology, clinical manifestations, and pathogenic genes deepens,various CC categorization systems based on diferent classifcation criteria have been proposed.Regrettably, the application of the CC category in clinical practice and scientifc research is limited. It is challenging to obtain preciseinformation that could guide the timely treatment decision-making for pediatric cataract patients or predict their prognosis from a specificCC classification. This review aims to discuss the statusquo of CC categorization systems and the potential directions for future research in this field, focusingon categorization principles and scientificapplication in clinical practice.Additionally, it aims to propose the potential directions for future research in this domain.