RETRACTED: An Approach for Cardiac Coronary Detection of Heart Signal Based on Harris Hawks Optimization and Multichannel Deep Convolutional Learning (Retracted Article)

被引：3

作者：

Alsafi, Haedar ^{[1
]}

Munilla, Jorge ^{[1
]}

Rahebi, Javad ^{[2
]}

机构：

[1] Malaga Univ, Dept Telecommun Engn, Malaga, Spain

[2] Istanbul Topkapi Univ, Dept Software Engn, Istanbul, Turkey

来源：

COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE | 2022年 / 2022卷

关键词：

EVOLUTIONARY ALGORITHM; ARRHYTHMIA DETECTION; DIAGNOSIS;

D O I：

10.1155/2022/7276028

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Automatic diagnosis of arrhythmia by electrocardiogram has a significant role to play in preventing and detecting cardiovascular disease at an early stage. In this study, a deep neural network model based on Harris hawks optimization is presented to arrive at a temporal and spatial fusion of information from ECG signals. Compared with the initial model of the multichannel deep neural network mechanism, the proposed model of this research has a flexible input length; the number of parameters is halved and it has a more than 50% reduction in computations in real-time processing. The results of the simulation demonstrate that the approach proposed in this research had a rate of 96.04%, 93.94%, and 95.00% for sensitivity, specificity, and accuracy. Furthermore, the proposed approach has a practical advantage over other similar previous methods.

引用

页数：17

共 38 条

[1] Automated identification of shockable and non-shockable life-threatening ventricular arrhythmias using convolutional neural network [J].