Cardiovascular Illness Detection and Categorization with Innovative Neural Networks

Year : 2025 | Volume : 12 | Issue : 02 | Page : 21 30
    By

    Anuradha S. Deokar,

  • Madhavi A. Pradhan,

  1. Assistant Professor, Department of Computer Engineering, All India Shri Shivaji Memorial Society (AISSMS) College of Engineering (Affiliated to Savitribai Phule Pune University), Pune, Maharashtra, India
  2. Associate Professor, Department of Computer Engineering, All India Shri Shivaji Memorial Society (AISSMS) College of Engineering (Affiliated to Savitribai Phule Pune University), Pune, Maharashtra, India

Abstract

Health-related problems are increasingly prevalent in modern-day societies and are significantly shaped by a multitude of factors encountered in everyday life. Among these, cardiovascular diseases have emerged as one of the primary causes of death on a global scale, posing serious challenges to public health systems. In response to this growing concern, the present study proposes a machine learning-based framework that is not only highly effective but also reliable and transparent in diagnosing cardiovascular conditions. The research adopts a hybrid approach by integrating five powerful techniques including the Support Vector Machine (SVM) algorithm and four advanced deep learning models: Convolutional Neural Network (CNN), Region-based Convolutional Neural Network (RCNN), and two versions of the You Only Look Once model, YOLOv3 and YOLOv4. These models were tested and evaluated using the publicly available Cardiac MRI Dataset obtained from Kaggle. Experimental results revealed that the proposed system achieves a remarkably high classification accuracy of 99.93%, outperforming existing cutting-edge methods and highlighting its potential for real-world clinical applications.

Keywords: Cardiovascular disease, CNN, support vector machine, region-based CNN, YOLO algorithm

[This article belongs to Journal of Artificial Intelligence Research & Advances ]

How to cite this article:
Anuradha S. Deokar, Madhavi A. Pradhan. Cardiovascular Illness Detection and Categorization with Innovative Neural Networks. Journal of Artificial Intelligence Research & Advances. 2025; 12(02):21-30.
How to cite this URL:
Anuradha S. Deokar, Madhavi A. Pradhan. Cardiovascular Illness Detection and Categorization with Innovative Neural Networks. Journal of Artificial Intelligence Research & Advances. 2025; 12(02):21-30. Available from: https://journals.stmjournals.com/joaira/article=2025/view=208166


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Regular Issue Subscription Original Research
Volume 12
Issue 02
Received 18/02/2025
Accepted 08/03/2025
Published 16/04/2025
Publication Time 57 Days
199

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