Diabetic retinopathy (DR) and diabetic macular edema (DME) remain major causes of vision loss among working-age adults. Artificial intelligence (AI), particularly deep learning, has gained attention in ophthalmic imaging, offering opportunities to improve both diagnostic accuracy and efficiency. This review examined applications of AI in DR and DME published between 2010 and 2025. A narrative search of PubMed and Google Scholar identified English-language, peer-reviewed studies, with additional screening of reference lists. Eligible articles evaluated AI algorithms for detection, classification, prognosis, or treatment monitoring, with study selection guided by PRISMA 2020. Of 300 records screened, 60 met the inclusion criteria. Most reported strong diagnostic performance, with sensitivities up to 96% and specificities up to 98% for detecting referable DR on fundus photographs. Algorithms trained on optical coherence tomography (OCT) data showed high accuracy for identifying DME, with area under the receiver operating characteristic curve (AUC) values frequently exceeding 0.90. Several models also predicted anti-vascular endothelial growth factor (anti-VEGF) treatment response and recurrence of fluid with encouraging results. Autonomous AI tools have gained regulatory approval and have been implemented in clinical practice, though performance can vary depending on image quality, device differences, and patient populations. Overall, AI demonstrates strong potential to improve screening, diagnostic consistency, and personalized care, but broader validation and system-level integration remain necessary.

Background and Objectives: The purpose of this study was to compare the effect of topical bromfenac and dexamethasone on the intraocular concentration of interleukin 6 (IL-6) and incidence of pseudophakic cystoid macular oedema (PCME) after cataract surgery in patients with non-proliferative diabetic retinopathy (NPDR). Materials and Methods: Ninety eyes of patients with mild-to-moderate NPDR that underwent phacoemulsification cataract surgery were divided into three groups. A detailed description of the clinical study protocol is described later in paper. In short, Group 1 received topical bromfenac (0.9 mg/mL), Group 2 dexamethasone (1 mg/mL), and Group 3 placebo, both preoperatively and postoperatively. Additionally, all patients received combined topical steroid and antibiotic drops (dexamethasone, neomycin and polymyxin B) 3 weeks postoperatively. On the day of the surgery, aqueous humour samples (0.1–0.2 mL) were obtained and IL-6 concentrations were analysed. Central foveal subfield thickness (CFT) measured using spectral-domain optical coherence tomography (SD-OCT) was analysed preoperatively and postoperatively. Results: There was no significant difference in IL-6 concentrations between groups. Postoperative CFT was significantly lower in the dexamethasone group compared to the placebo group. In addition, the correlation between IL-6 and CFT was statistically significant in the dexamethasone group. No patient developed PCME in any of the three groups. No adverse events were reported during the study. Conclusion: Topical bromfenac and dexamethasone have no significant effect on intraocular IL-6 concentration in patients with NPDR. Topical bromfenac is not more effective than topical dexamethasone in reducing postoperative CFT in patients with NPDR.

Fuchs endothelial corneal dystrophy (FECD) is the most common corneal endothelial dystrophy. It is characterized by the progressive loss of corneal endothelial cells (CECs), guttae formation on the Descemet membrane, and corneal edema, leading to visual impairment. Corneal transplantation remains the standard treatment, but it has limitations such as donor shortages, infection risk, and graft rejection. Rho-kinase (ROCK) inhibitors have emerged as a promising pharmacological alternative. These agents promote CEC proliferation, migration, and adhesion while inhibiting apoptosis and enhancing corneal endothelial wound healing. Several studies have demonstrated the efficacy of ROCK inhibitors in improving corneal clarity and endothelial function, particularly when used as an adjunct to Descemet Stripping Only (DSO) surgery. Additionally, they show potential in preventing corneal edema in FECD patients undergoing cataract surgery. The methodology involved a literature search through the PubMed and Medline databases using relevant keywords. Only peer-reviewed articles in English were included, with additional references from selected articles reviewed to ensure comprehensive coverage. ROCK inhibitors offer a novel pharmacological approach to managing FECD. They have shown potential in promoting endothelial cell regeneration and improving corneal functIion. Despite promising results, further research is required to determine ROCK inhibitors’ long-term safety, optimal dosing, and efficacy in surgical and non-surgical FECD patients. Their potential to delay or prevent corneal transplantation represents a significant advancement in FECD management.

Pseudophakic bullous keratopathy (PBK) is a vision-threatening corneal complication following cataract surgery, characterised by progressive endothelial cell loss, persistent corneal oedema, and painful epithelial bullae, leading to impaired vision. Corneal transplantation, either penetrating or endothelial keratoplasty, remains the primary treatment but faces challenges such as donor tissue shortages, graft rejection, and limited graft longevity. Recently, Rho-kinase (ROCK) inhibitors have emerged as promising pharmacological alternatives. These agents enhance corneal endothelial cell proliferation, migration, and adhesion, suppress apoptosis, and promote corneal deturgescence and wound healing. Several preclinical and clinical studies have demonstrated the efficacy of ROCK inhibitors in improving corneal clarity, endothelial function, and visual acuity in PBK. Their use has been associated with reductions in corneal oedema, improved endothelial cell density, and delayed or prevented the need for corneal transplantation. A systematic literature search of PubMed, Scopus, and Web of Science databases was conducted, restricted to peer-reviewed English-language articles, ensuring comprehensive coverage. ROCK inhibitors represent a novel pharmacological strategy for PBK prevention and management, potentially reducing dependency on donor grafts. Further research is needed to determine long-term safety, optimal dosing, and efficacy.

Artificial intelligence (AI) is being investigated across the cataract care pathway, but the maturity of the evidence varies substantially between technical benchmark studies, externally validated models, prospective clinical evaluations and tools used in routine care. This narrative review critically summarises AI applications in cataract detection, intraocular lens (IOL) power calculation, perioperative risk assessment, intraoperative support and postoperative follow‐up, with particular emphasis on evidence quality, external validity and clinical readiness. A structured search of PubMed/MEDLINE was conducted for English‐language publications from 1 January 2018 through 31 March 2025, with selective retention of earlier seminal studies relevant to cataract risk prediction, force feedback and ophthalmic robotics. Evidence was classified by maturity, from technical proof of concept and retrospective internal validation to external or multicentre validation, prospective clinical evaluation and demonstrated workflow or patient‐level benefit. The strongest evidence for cataract detection comes from large externally validated image‐based models, whereas smartphone systems remain sensitive to image quality, case mix and deployment setting. Data‐driven IOL formulas can improve refractive prediction in selected datasets, but comparisons are affected by constant optimisation, axial‐length distribution, IOL model, measurement device and paired‐eye dependence. Intraoperative AI remains dominated by phase recognition, segmentation and technical performance assessment, with limited evidence of direct clinical benefit. Postoperative conversational AI has reached multicentre prospective clinical evaluation, although safety depends on escalation pathways, human oversight and local workflow design. Clinical translation of AI in cataract care is therefore emerging but uneven: a limited number of applications have reached external or prospective clinical validation, while many remain retrospective or technical proof‐of‐concept systems. Future adoption should be based on external validation, transparent reporting, prospective clinical utility, postdeployment monitoring and clear regulatory and medicolegal accountability rather than benchmark performance alone.