Abstract

Glaucoma is progressive and silent, it presents substantial hurdles to early detection and successful therapy. Glaucoma is one of the world’s leading causes of irreversible blindness. Novel developments in diagnostic technology have encouraging prospects for tackling these obstacles and enhancing patient results. An overview of the most recent advancements in glaucoma diagnosis, such as imaging modalities, functional evaluations, and artificial intelligence (AI) applications, is given in this abstract. The exact assessment of optic nerve anatomy and visual field function made possible by optical coherence tomography (OCT), confocal scanning laser ophthalmoscopy (CSLO), and frequency-doubling technology (FDT) perimetry helps in early illness detection and progression tracking. Large-scale imaging and clinical data sets are used to train AI-driven algorithms, which improve diagnostic precision and enable individualized risk assessment and treatment planning. With earlier intervention, more individualized care, and better long-term visual results possible, these diagnostic advancements have the potential to completely transform the diagnosis and treatment of glaucoma. To fully appreciate the clinical benefit of these advances, however, standardization, integration, and validation difficulties need to be addressed. To improve the quality of treatment for patients with glaucoma and expedite the translation of these discoveries into clinical practice, industry partners, doctors, and researchers must work together.