FAST PREDICTION OF KERATACONUS DETECTION USING SVM AND CORNEAL FEATURE

Adhil Naseem; Harish Venu; Ashique Soloman Paul; Akhil PS; Athulya MS; Abhin Prakash MP

FAST PREDICTION OF KERATACONUS DETECTION USING SVM AND CORNEAL FEATURE

April 2024

Vol-10, Issue-2

Paper ID: 23087

ISSN: 2395-4396

Downloads: 0

Abstract & Details

Research Area

Computer Engineering

Keywords

SVM (Support Vector Machine) Keratoconus prevalence machine learning algorithms Matlab corneal integrated discriminating preclinical stand-alone-software.

Abstract

Keratoconus is a disease were approximately one in 2,000 people globally suffer with keratoconus in one eye or both the eyes. It is commonly linked to a decline in visual acuity. In order to stop the disease's progression and eyesight loss, new instruments that can identify the condition early on are desperately needed, especially considering how common it is. This project aims to create and evaluate a machine learning system capable of early keratoconus detection. In order to identify keratoconus, a number of machine learning algorithms were used. The methods were then evaluated using actual medical data. 25 distinct machine learning models were implemented in Matlab, yielding accuracy ranging from 62% to 94.0%. A support vector machine (SVM) technique using a subset of the eight corneal parameters with the strongest discriminating power achieved the maximum accuracy level of 94%. The suggested model could help doctors identify keratoconus and assess corneal condition, which are difficult tasks to perform by subjective assessments, especially in the preclinical and early stages of the disease. The technique for evaluating the cornea and identifying early-stage keratoconus can be stand-alone-software or integrated into corneal imaging devices.

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Author Information

#	Name	Institute / Affiliation
1	Adhil Naseem	KKMMPTC Mala
2	Harish Venu	KKMMPTC Mala
3	Ashique Soloman Paul	KKMMPTC Mala
4	Akhil PS	KKMMPTC Mala
5	Athulya MS	KKMMPTC Mala
6	Abhin Prakash MP	KKMMPTC Mala

How to Cite

Use the following formats to cite this article in your research.

APA Style

Naseem, Adhil, Venu, Harish, Paul, Ashique Soloman, PS, Akhil, MS, Athulya, & MP, Abhin Prakash (2024). FAST PREDICTION OF KERATACONUS DETECTION USING SVM AND CORNEAL FEATURE. International Journal of Advance Research and Innovative Ideas In Education, 10(2), 2634-2641.

MLA Style

Naseem, Adhil, et al. "FAST PREDICTION OF KERATACONUS DETECTION USING SVM AND CORNEAL FEATURE." International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 2, 2024, pp. 2634-2641.

IEEE Style

Adhil Naseem, Harish Venu, Ashique Soloman Paul, Akhil PS, Athulya MS, and Abhin Prakash MP, "FAST PREDICTION OF KERATACONUS DETECTION USING SVM AND CORNEAL FEATURE," International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 2, pp. 2634-2641, 2024.

Vancouver Style

Naseem Adhil, Venu Harish, Paul Ashique Soloman, PS Akhil, MS Athulya, MP Abhin Prakash. FAST PREDICTION OF KERATACONUS DETECTION USING SVM AND CORNEAL FEATURE. International Journal of Advance Research and Innovative Ideas In Education. 2024;10(2):2634-2641.

Harvard Style

Naseem, Adhil, Venu, Harish, Paul, Ashique Soloman, PS, Akhil, MS, Athulya, & MP, Abhin Prakash (2024) 'FAST PREDICTION OF KERATACONUS DETECTION USING SVM AND CORNEAL FEATURE', International Journal of Advance Research and Innovative Ideas In Education, 10(2), pp. 2634-2641.

Chicago Style

Naseem, Adhil, et al. "FAST PREDICTION OF KERATACONUS DETECTION USING SVM AND CORNEAL FEATURE." International Journal of Advance Research and Innovative Ideas In Education 10, no. 2 (2024): 2634-2641.

Turabian Style

Naseem, Adhil, et al. "FAST PREDICTION OF KERATACONUS DETECTION USING SVM AND CORNEAL FEATURE." International Journal of Advance Research and Innovative Ideas In Education 10, no. 2 (2024): 2634-2641.