DR. JYOTI MATALIA

Dr. POOJA GHALLA, Dr.Pratibha Panmand, Dr.Dr. SHETTY BHUJANG K.

Abstract

Purpose: Current pandemic has increased incidence of myopia, its progression with significant reduction in quality of life. Additional integrated screening and predictive strategies beyond myopia are required to reduce this burden.

Methods: This study developed an artificial intelligence (AI)-based prediction method that integrated biometry, retinoscopy, corneal biomechanics, corneal tomography, tear fluid dopamine level, hereditary and life-based information in a cohort of 205 children (emmetropes 50; myopes 155) in the prediction of myopia incidence and progression.

Results: Combination of corneal biomechanics and topographic information with biometry (axial length) improved identification and prediction of myopia and progression. Significant reduction in the levels of tear fluid dopamine levels was observed in myopes.

Conclusion: AI-assisted processing of extended cohort-based information will aid in the development of early detection, prevention and management strategy for myopia.

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