SVM based Prediction Model for Primary Open-Angle Glaucoma with Optic Nerve Vasoconstriction Based on Age-Related Degeneration & Environmental Pollution

Authors

  • V. Satya Aruna Research Scholar, Dept. of Computer Science & Engineering, Koneru Lakshmaiah Education Foundation, Greenfields, Vaddeswaram, Guntur-522502
  • B. Chaitanya Krishna Dept. of Computer Science & Engineering, Koneru Lakshmaiah Education Foundation, Greenfields, Vaddeswaram, Guntur-522502

Keywords:

Support Vector Machine, Primary Open Angle Glaucoma, Age related Degeneration, Vasoconstriction, Optic Nerve Head Morphology, Intraocular Pressure, Vascular Reactivity, Environmental Pollution, Hyper Plane

Abstract

This research aims to develop a predictive model for primary open-angle glaucoma (POAG) using the Support Vector Machine (SVM) algorithm. The study integrates age-related degeneration, pollution effects on eyes, and vasoconstriction at the optic nerve head. Diverse age groups will be analyzed using clinical records, imaging data, and environmental parameters. SVM will identify patterns and evaluate features such as optic nerve head morphology, intraocular pressure, age, pollution exposure, and vascular reactivity. The proposed model seeks to enhance early POAG detection and provide insights into the association between pollution and glaucoma. Anticipated outcomes include a robust SVM- based prediction model for POAG, facilitating risk assessment and early intervention. This research contributes to ophthalmology and machine learning, enabling personalized glaucoma risk assessment and targeted healthcare interventions.

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Published

24.03.2024

How to Cite

Aruna , V. S. ., & Krishna, B. C. . (2024). SVM based Prediction Model for Primary Open-Angle Glaucoma with Optic Nerve Vasoconstriction Based on Age-Related Degeneration & Environmental Pollution. International Journal of Intelligent Systems and Applications in Engineering, 12(20s), 462–468. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/5158

Issue

Vol. 12 No. 20s (2024)

Section

Research Article

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