Neural Network Algorithm Based on LVQ for Myocardial Infarction Detection and Localization Using Multi-Lead ECG Data
Source abstract
Abstract
Myocardial infarction (MI) is one of the leading causes of death globally among cardiovascular diseases, necessitating modern and accurate diagnostics for cardiac patient conditions. Among the available functional diagnostic ... | Find, read and cite all the research you need on Tech Science Press
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: ECG Monitoring and Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (24)
Show source-provided references
1. Global cardiovascular diseases death rate prediction10.1016/j.cpcardiol.2023.101622 ↗
2. Mechanical complications of acute myocardial infarction: a review10.1001/jamacardio.2020.3690 ↗
3. Time-frequency approach to ECG classification of myocardial infarction10.1016/j.compeleceng.2020.106621 ↗
4. A new electrocardiographic pattern indicating inferior myocardial infarction10.1016/j.jelectrocard.2020.04.008 ↗
5. Accurate detection of myocardial infarction using non linear features with ECG signals10.1007/s12652-020-02536-4 ↗
6. Echocardiography in acute myocardial infarction10.1016/0002-9149(75)90859-0 ↗
7. Early myocardial infarction detection over multi-view echocardiography10.1016/j.bspc.2023.105448 ↗
8. Identification of patients with acute myocardial infarction based on coronary CT angiography: the value of pericoronary adipose tissue radiomics10.1007/s00330-022-08812-5 ↗
9. Biomarkers of acute myocardial infarction: diagnostic and prognostic value. Part 1
10. Past, present, and future of blood biomarkers for the diagnosis of acute myocardial infarction-promises and challenges10.3390/diagnostics11050881 ↗
11. Machine learning for ECG diagnosis and risk stratification of occlusion myocardial infarction10.1038/s41591-023-02396-3 ↗
12. Explainable prediction of acute myocardial infarction using machine learning and shapley values10.1109/ACCESS.2020.3040166 ↗
13. Deep learning for detecting and locating myocardial infarction by electrocardiogram: a literature review10.3389/fcvm.2022.860032 ↗
14. Detection of myocardial infarction using hybrid models of convolutional neural network and recurrent neural network10.3390/biomedinformatics3020033 ↗
15. Wearable ECG device and machine learning for heart monitoring10.3390/s24134201 ↗
16. Multi-label ECG signal classification based on ensemble classifier10.1109/ACCESS.2020.3004908 ↗
17. MCA-net: a multi-task channel attention network for Myocardial infarction detection and location using 12-lead ECGs10.1016/j.compbiomed.2022.106199 ↗
18. An efficient method for detection and localization of myocardial infarction
19. A multi-dimensional association information analysis approach to automated detection and localization of myocardial infarction10.1016/j.engappai.2020.104092 ↗
20. Portable ECG monitoring system
21. Optimization of resources in intelligent electronic health systems based on Internet of Things to predict heart diseases via artificial neural network10.1016/j.heliyon.2024.e32090 ↗
22. Development and validation of deep learning ECG-based prediction of myocardial infarction in emergency department patients10.1038/s41598-022-24254-x ↗
23. Explainable detection of myocardial infarction using deep learning models with Grad-CAM technique on ECG signals10.1016/j.compbiomed.2022.105550 ↗
24. Physiobank, physiotoolkit, and physionet: components of a new research resource for complex physiologic signals10.1161/01.CIR.101.23.e215 ↗