A robustness evaluation of machine learning algorithms for ECG myocardial infarction detection

M Sraitih, Y Jabrane, A Hajjam El Hassani - Journal of Clinical Medicine, 2022 - mdpi.com
An automatic electrocardiogram (ECG) myocardial infarction detection system needs to
satisfy several requirements to be efficient in real-world practice. These requirements, such …

[PDF][PDF] Convolution-Based Heterogeneous Activation Facility for Effective Machine Learning of ECG Signals.

S Narayanan - Computers, Materials & Continua, 2023 - cdn.techscience.cn
ABSTRACT Machine Learning (ML) and Deep Learning (DL) technologies are
revolutionizing the medical domain, especially with Electrocardiogram (ECG), by providing …

Exploring Machine Learning Algorithms for Myocardial Infarction Diagnosis

S El Omary, S Lahrache… - … Conference on Intelligent …, 2024 - ieeexplore.ieee.org
Cardiovascular diseases, including Myocardial Infarction, remain a leading cause of global
morbidity and mortality [1]. Myocardial Infarction is a medical condition characterized by …

[HTML][HTML] Automatic electrocardiograph diagnosis of myocardial ischemia with support vector machine

D Zhong, L Huang, S Jin, Y An, S Zhu, J Li - Digital Medicine, 2023 - journals.lww.com
Background: Myocardial ischemia is a severe cardiac disease and it happens when the
heart's blood flow is insufficient, which impairs its capacity to operate correctly and causes …

Linear and nonlinear features for myocardial infarction detection using support vector machine on 12-lead ECG recordings

WJ Arenas, ML Zequera, M Altuve… - 8th European Medical and …, 2021 - Springer
The development of non-invasive techniques to assess cardiovascular risks has grown
rapidly. In this sense, a multi-lead electrocardiogram (ECG) provides useful information to …