Abstract: Glaucoma, characterized by elevated intraocular pressure (IOP) and optic nerve damage, encompasses various types with distinct pathogenic mechanisms. Research has identified key factors influencing glaucoma, such as environmental influences, stress, and age-related factors. This study focuses on the impact of stress on IOP levels in glaucoma patients and evaluates different machine learning (ML) models for enhanced glaucoma detection using OCT and Color Fundus images. Additionally, I explore the environmental implications of elevated IOP, emphasizing lifestyle interventions like yoga to potentially reduce IOP levels. As a practical application, I propose the development of a dedicated mobile app as a digital wellness program for glaucoma patients.
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