Cardiovascular Disease Detection from Retinal  Image using Machine Learning

Sahyadri Prakash pukale; Hritika Gupta; Harsha Nagesh Moger; Amith P Shetty; HarishKumar B T

Cardiovascular Disease Detection from Retinal Image using Machine Learning

May 2024

Vol-10, Issue-3

Paper ID: 24064

ISSN: 2395-4396

Downloads: 0

Abstract & Details

Research Area

Computer Science of Engineering

Keywords

Keywords— Cardiovascular deep learning retinal images feature extraction machine learning transfer learning.

Abstract

Abstract—Cardiovascular Diseases (CVDs) are a predominant cause of mortality worldwide, underscoring the need for innovative diagnostic approaches that enhance early detection and effective management. This paper proposes a machine learning based approach to analyze retinal images for cardiovascular disease prediction. Using retinal images for heart disease prediction being a non-invasive and easily accessible method would allow for faster, cheaper, and overall accessible diagnosis tools especially necessary for low-income areas, instead of stress inducing fasting blood tests, leading to overall earlier diagnosis and intervention. We employ a pre-trained neural network model, adapted to analyze images namely inception v3 and fine-tune it to analyze retinal images to classify heart disease risk into 5 classes, using the structural changes in the retinal microvasculature.

License

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Author Information

#	Name	Institute / Affiliation
1	Sahyadri Prakash pukale	Bangalore Institute of Technology Bangalore, India
2	Hritika Gupta	Bangalore Institute of Technology Bangalore, India
3	Harsha Nagesh Moger	Bangalore Institute of Technology
4	Amith P Shetty	Bangalore Institute of Technology Bangalore, India
5	HarishKumar B T	Bangalore Institute of Technology Bangalore, India

How to Cite

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

APA Style

pukale, Sahyadri Prakash, Gupta, Hritika, Moger, Harsha Nagesh, Shetty, Amith P, & T, HarishKumar B (2024). Cardiovascular Disease Detection from Retinal Image using Machine Learning. International Journal of Advance Research and Innovative Ideas In Education, 10(3), 3021-3027.

MLA Style

pukale, Sahyadri Prakash, et al. "Cardiovascular Disease Detection from Retinal Image using Machine Learning." International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 3, 2024, pp. 3021-3027.

IEEE Style

Sahyadri Prakash pukale, Hritika Gupta, Harsha Nagesh Moger, Amith P Shetty, and HarishKumar B T, "Cardiovascular Disease Detection from Retinal Image using Machine Learning," International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 3, pp. 3021-3027, 2024.

Vancouver Style

pukale Sahyadri Prakash, Gupta Hritika, Moger Harsha Nagesh, Shetty Amith P, T HarishKumar B. Cardiovascular Disease Detection from Retinal Image using Machine Learning. International Journal of Advance Research and Innovative Ideas In Education. 2024;10(3):3021-3027.

Harvard Style

pukale, Sahyadri Prakash, Gupta, Hritika, Moger, Harsha Nagesh, Shetty, Amith P, & T, HarishKumar B (2024) 'Cardiovascular Disease Detection from Retinal Image using Machine Learning', International Journal of Advance Research and Innovative Ideas In Education, 10(3), pp. 3021-3027.

Chicago Style

pukale, Sahyadri Prakash, et al. "Cardiovascular Disease Detection from Retinal Image using Machine Learning." International Journal of Advance Research and Innovative Ideas In Education 10, no. 3 (2024): 3021-3027.

Turabian Style

pukale, Sahyadri Prakash, et al. "Cardiovascular Disease Detection from Retinal Image using Machine Learning." International Journal of Advance Research and Innovative Ideas In Education 10, no. 3 (2024): 3021-3027.