Citation

Hari, Kamya and Rajeshwar, Kruthi and Praba, Bashyam and Nagarajan, Deivanayagampillai (2026) Application of graph energy in glaucoma detection using machine learning techniques. In: Data-driven Decision Making and Soft Computing. CRC Press, pp. 22-39. ISBN 978-100363483-6, 978-104106297-4, 978-104106314-8

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Abstract

Glaucoma is a collection of ocular disorders that harm the optic nerve, an essential component for visual acuity. Typically, this disorder occurs due to elevated pressure levels inside the eye. Glaucoma is a leading cause of irreversible blindness in our aging society, with a projected number of patients of 112 million by 2040 [1]. Hence, early detection of glaucoma is crucial in preventing further damage to the eye. However, manual diagnosis of glaucoma can be time-consuming and subjective, as it relies on the expertise of the ophthalmologist.

Item Type:	Book Section
Uncontrolled Keywords:	Computer Science, Engineering & Technology
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Engineering and Technology (FET)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	03 Sep 2026 01:44
Last Modified:	03 Sep 2026 01:44
URII:	http://shdl.mmu.edu.my/id/eprint/16566

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