REVIEW ARTICLE
An Exhaustive Study on Deep Neural Network-based Prediction of Heart Diseases and its Interpretations
Jothiaruna Nagaraj1, Anny Leema A.1, *
Article Information
Identifiers and Pagination:
Year: 2023Volume: 17
Issue: Suppl-1, M2
E-location ID: e187412072210310
Publisher ID: e187412072210310
DOI: 10.2174/18741207-v16-e221031-2022-HT27-3589-16
Article History:
Received Date: 13/6/2022Revision Received Date: 2/8/2022
Acceptance Date: 22/8/2022
Electronic publication date: 2/1/2023
Collection year: 2023
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Cardiovascular disease prediction is important in day-to-day life. A tool to diagnose cardiovascular diseases is an Electrocardiogram (ECG), which records electrical activities happening in the heart through a wave. A determination is made by checking the wave changes in an ECG. Predicting wave changes and diagnosing the disease requires domain expertise like cardiologists/physicians. Deep Neural Network techniques extract the features accurately and automatically predict the type of disease. This article lists different types of cardiac disorders, and parallelly different disease interpretations of all types of diseases are discussed to manually identify the disease type; segmentation of leads, pre-trained models, and different detection techniques are discussed to predict the type of diseases from an ECG image. Finally, this article discussed the different challenges in predicting heart diseases, and solutions to some of the challenges are given.