Computer-aided detection and diagnosis in ECG signals for heart diseases are gaining
increasing attention. However, developing and selecting the highly performing diagnostic …

Feature selection by removing redundant and noisy features is one of the crucial steps in the
classification problem. This paper presents a novel chaotic-based divide-and-conquer …

This work aimed to review different Computer-Aided Detection (CAD) systems that were
proposed as alternative means to replace the tedious and erroneous double reading …

Electrocardiogram (ECG) is a P, QRS and T wave demonstrating the electrical activity of the
heart. Feature extraction and segmentation in ECG plays a significant role in diagnosing …

This paper proposes a hybrid model to classify cardiac arrhythmias and select their features
in an optimal way. In the proposed model, the Genetic Algorithm was used to optimally …

Among the various applications of machine learning in Biomedical Engineering, one of the
ares of focus for researchers is its application in biomedical signal processing to extract …

Cardio‐cerebrovascular disease is one of the malignant diseases with the highest morbidity
and mortality in the world. Medical research shows that the factors that induce heart blood …

This paper explores the potential of Global Navigation Satellite Systems (GNSS) multipath
signals for soil moisture retrieval, specifically focusing on Navigation with Indian …

Bioengineering sign is responsible for processing biosignal acquisition preprocessing and
evaluation. It is used so that physicians can decide on valuable information. New methods of …

Purpose The electrocardiograms analysis helps cardiologists to diagnosis different cardiac
disorders. In this paper, we have proposed a new training algorithm of a multilayer …