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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).Review Citation - WoS: 1Citation - Scopus: 1Diagnostic Use of Circulating Cells and Sub-Cellular Bio-Particles(Pergamon-elsevier Science Ltd, 2024) Tevlek, AtakanIn the bloodstream or other physiological fluids, "circulating cells and sub-cellular bio-particles" include many microscopic biological elements such as circulating tumor cells (CTCs), cell-free DNA (cfDNA), exosomes, microRNAs, platelets, immune cells, and proteins are the most well-known and investigated. These structures are crucial biomarkers in healthcare and medical research for the early detection of cancer and other disorders, enabling treatment to commence before the onset of clinical symptoms and enhancing the efficacy of treatments. As the size of these biomarkers to be detected decreases and their numbers in body fluids diminishes, the detection materials, ranging from visual inspection to advanced microscopy techniques, begin to become smaller, more sensitive, faster, and more effective, thanks to developing nanotechnology. This review first defines the circulating cells and subcellular bio-particles with their biological, physical, and mechanical properties and second focuses on their diagnostic importance, including their most recent applications as biomarkers, the biosensors that are utilized to detect them, the present obstacles that must be surmounted, and prospective developments in the domain. As technology advances and biomolecular pathways are deepens, diagnostic tests will become more sensitive, specific, and thorough. Finally, integrating recent advances in the diagnostic use of circulating cells and bioparticles into clinical practice is promising for precision medicine and patient outcomes.
