Glaucoma prediction using machine learning

Prof. Vinutha N; Pranathi HS; Sri Raksha RK; Ameesha BC; Sujan PR

Glaucoma prediction using machine learning

May 2025

Vol-11, Issue-3

Paper ID: 26526

ISSN: 2395-4396

Downloads: 0

Abstract & Details

Research Area

Computer Science Engineering

Keywords

Glaucoma Optic nerve Retinal fundus images Blindness Ophthalmology Machine Learning Deep Learning MobileNetV2 Google Colab Softmax python Screening Data bias

Abstract

Glaucoma is a progressive and chronic eye disease that causes damage to the optic nerve, which may result in irreversible blindness if diagnosed and treated too late. Conventional diagnostic procedures need specialized hardware and clinical knowledge, which are not always available in all areas. To overcome this, we introduce an automated glaucoma detection system using deep learning, which can process retinal fundus photographs and categorize them as normal and stages of glaucoma advanced with high accuracy. The system leverages the use of Convolutional Neural Networks (CNNs), optimized for visual pattern classification tasks, to extract and analyze glaucoma-related features such as optic disc cupping and thinning of the nerve fibers. Before images are classified, they go through preprocessing procedures such as resizing, pixel normalization, and contrast enhancement to enhance model performance. The trained model gives classification probabilities, which are displayed as bar charts for improved interpretability. The solution is incorporated within a web-based platform developed with IJIUStreamlit, offering a user-friendly interface for image upload, result viewing, and medical recommendations. An AI-driven chatbot also helps users interpret the results, promotes regular checkups, and advises them to get immediate attention when needed. The system supports remote screening, making it highly applicable in rural and underserved healthcare settings. Experimental evaluation demonstrates the model’s strong performance, outperforming several baseline techniques and achieving reliable classification even with noisy or lower quality images. By combining deep learning, intuitive UI, and intelligent assistance, the system enhances early detection capabilities and supports clinical workflows for ophthalmologists and general healthcare providers.

License

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Author Information

#	Name	Institute / Affiliation
1	Prof. Vinutha N	Vidya Vikas Institute of Engineering & Technology, karnataka, India.
2	Pranathi HS	Vidya Vikas Institute of Engineering & Technology, karnataka, India.
3	Sri Raksha RK	Vidya Vikas Institute of Engineering & Technology, karnataka, India.
4	Ameesha BC	Vidya Vikas Institute of Engineering & Technology, karnataka, India.
5	Sujan PR	Vidya Vikas Institute of Engineering & Technology, karnataka, India.

How to Cite

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

APA Style

N, Prof. Vinutha, HS, Pranathi, RK, Sri Raksha, BC, Ameesha, & PR, Sujan (2025). Glaucoma prediction using machine learning. International Journal of Advance Research and Innovative Ideas In Education, 11(3), 1467-1472.

MLA Style

N, Prof. Vinutha, et al. "Glaucoma prediction using machine learning." International Journal of Advance Research and Innovative Ideas In Education, vol. 11, no. 3, 2025, pp. 1467-1472.

IEEE Style

Prof. Vinutha N, Pranathi HS, Sri Raksha RK, Ameesha BC, and Sujan PR, "Glaucoma prediction using machine learning," International Journal of Advance Research and Innovative Ideas In Education, vol. 11, no. 3, pp. 1467-1472, 2025.

Vancouver Style

N Prof. Vinutha, HS Pranathi, RK Sri Raksha, BC Ameesha, PR Sujan. Glaucoma prediction using machine learning. International Journal of Advance Research and Innovative Ideas In Education. 2025;11(3):1467-1472.

Harvard Style

N, Prof. Vinutha, HS, Pranathi, RK, Sri Raksha, BC, Ameesha, & PR, Sujan (2025) 'Glaucoma prediction using machine learning', International Journal of Advance Research and Innovative Ideas In Education, 11(3), pp. 1467-1472.

Chicago Style

N, Prof. Vinutha, et al. "Glaucoma prediction using machine learning." International Journal of Advance Research and Innovative Ideas In Education 11, no. 3 (2025): 1467-1472.

Turabian Style

N, Prof. Vinutha, et al. "Glaucoma prediction using machine learning." International Journal of Advance Research and Innovative Ideas In Education 11, no. 3 (2025): 1467-1472.