Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{160814,
        author = {Rexeena.x and Haritha.S and Nimi.S},
        title = {Deep Learning Based detection of Heart Diseases: A comprehensive Review and Future Directions},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {1},
        pages = {1293-1299},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=160814},
        abstract = {Heart diseases are a leading cause of morbidity and mortality worldwide, necessitating accurate and timely diagnosis for effective treatment. In recent years, deep learning techniques, particularly neural networks, have shown promising results in various medical applications, including the detection and diagnosis of heart diseases. This paper presents a comprehensive review of the existing literature on the use of neural networks for identifying heart diseases, focusing on the different approaches, datasets, and evaluation metrics employed. Furthermore, this review identifies key challenges and discusses potential future directions in this rapidly evolving field.},
        keywords = {Convolutional Neural Networks, Deep Learning, Hybrid Architecture, Recurrent Neural Network. },
        month = {},
        }