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International Journal of Current Bio-Medical Engineering - IJCBE

PRIMARY OPEN-ANGLE GLAUCOMA SEVERITY PREDICTION USING DEEP LEARNING TECHNIQUE


Glaucoma is a neuro optical disorder that lead to blindness over a period of time. In recent years, studies have revealed that diabetic patients are more common victims of glaucoma. The present research aims to investigate the relationships between intraocular pressure (IOP), refractive error, and primary open-angle glaucoma (POAG) in the wheatish population. Population-based research provide important information on the prevalence and hazards for glaucoma, such eye refractive defects. At low IOP stages, the correlation between glaucoma and myopia is strong, and it gradually decreases as IOP rises. A Deep learning tool is developed to analyze the severity of glaucoma using fundus image. According to this research, the association between IOP and glaucoma is strong at low mean values of 15±3.23 level and gradually weakens as IOP increases in the wheatish population, reaching 17.59±3.33 for PACG, 18.85±1.20 for POAG, 18.59±2.52 for PIGM, and 19.12±1.42 for OH. With increasing IOP, the glaucoma image in myopic eyes degraded, and no correlation with IOP ≥35 mmHg has been found.