Year: 2025
Type: article
Abstract: Since Cardiac and vascular conditions rank among major cause of death around the world, sophisticated diagnostic methods are required for both early identification and prevention [13] Libby et al. In order to predict heart functionality with high accuracy, we present a novel deep learning model in this study that uses heart acoustic inputs. Due to the hybrid conventional neural network (CNN) and architecture with a gate with a gate with a re-unit (BIGRU) architecture, the recommended model learns the time and spatial features of heart sound records. In contrast to conventional machine learning methods, approach improves a small diagnosis of heart abnormalities with improved diagnostic accuracy.
Author: Indumathi R
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4409144313