2 results
Search Results
Now showing 1 - 2 of 2
Article Revolutionizing Glaucoma Care: Harnessing Artificial Intelligence for Precise Diagnosis and Management(Gazi Eye Foundation, 2025) Ucgul, A.Y.; Aktaş, Z.Glaucoma is a leading cause of irreversible blindness worldwide, necessitating early detection and effective management to prevent vision loss. Recent advancements in artificial intelligence (AI) have revolutionized glaucoma care by enhancing diagnostic accuracy, monitoring disease progression, and personalizing treatment strategies. AI models, including machine learning and deep learning algorithms, have demonstrated exceptional performance in analyzing fundus photography, optical coherence tomography, and visual field data, surpassing traditional diagnostic methods. Convolutional neural networks have shown high sensitivity and specificity in detecting glaucomatous changes, while vision transformers and hybrid AI models further refine risk assessment and prognosis. Additionally, AI-powered monitoring systems utilizing multi-modal data integration allow for more precise prediction of disease progression and the need for surgical intervention. The incorporation of AI into telemedicine and wearable intraocular pressure sensors extends glaucoma management to remote and underserved populations. Despite these advancements, challenges remain, including issues related to algorithm generalizability, data standardization, bias, and ethical concerns regarding AI-driven clinical decision-making. To maximize AI’s potential in glaucoma care, further interdisciplinary research, regulatory oversight, and multi-center validation studies are needed. By addressing these challenges, AI can be effectively integrated into clinical practice, leading to improved early detection, enhanced treatment strategies, and more personalized patient care. The future of AI in glaucoma management holds great promise, paving the way for a more data-driven and patient-centered approach to combating this sight-threatening disease. © 2024 The author(s).Book Part Glaucoma Associated With Non-Acquired Ocular Disorders(Springer International Publishing, 2024) Aktas, Z.; Ucgul, A.Y.; Ikiz, G.D.Congenital ocular disorders with a significant potential to develop glaucoma include Axenfeld-Rieger syndrome, Peters anomaly, and aniridia. Other ocular conditions such as microcornea, congenital ectropion uveae, oculodermal melanocytosis, posterior polymorphous dystrophy, congenital iris hypoplasia, and various congenital retinal diseases can also be complicated by glaucoma development. The risk of developing glaucoma in Axenfeld-Rieger syndrome, Peters anomaly, and aniridia is notably high (50-75%) compared to the other condition where this risk is relatively lower (10-15%). Glaucoma secondary to these congenital disorders tends to have a severe clinical course and be more resistant to anti-glaucomatous therapies compared to primary congenital glaucoma. Managing intraocular pressure (IOP) can be challenging after treating concomitant anomalies such as cataract and corneal opacity. Furthermore, IOP-lowering procedures, such as drainage tube implantation, may lead to corneal decompensation and cataract development. Given the complexity of these conditions, a multidisciplinary approach is essential for effective treatment of these diseases. Long-term follow-up is crucial to monitor for the development of glaucoma. While topical anti-glaucoma medications are mostly used as the first-line therapy, many cases ultimately require surgical interventions, such as trabeculectomy and tube implant surgery. Transscleral diode cyclophotocoagulation can be an appropriate treatment option for patients with limited or no visual potential. Often, multiple interventions are necessary to achieve adequate IOP control. In addition to managing IOP, amblyopia rehabilitation is a critical component of the lifelong treatment of these challenging cases. This comprehensive approach ensures that both the ocular and visual development needs of individuals with these challenging conditions are addressed effectively. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
