The extensive growth of data in the health domain has increased the utility of Deep Learning
in health. Deep learning is a highly advanced successor of artificial neural networks, having …

Shifting from fossil to clean energy sources is a major global challenge, but in particular for
those countries with substantial fossil-fuel reserves and economies depending on fossil-fuel …

There are many sources of interference encountered in the electroencephalogram (EEG)
recordings, specifically ocular, muscular, and cardiac artifacts. Rejection of EEG artifacts is …

One of the most common diseases among women is breast cancer, the early diagnosis of
which is of paramount importance. Given the time-consuming nature of the diagnosis …

The aim of this study is to investigate the feasibility of identifying and applying quantitative
imaging features computed from ultrasound images of athymic nude mice to predict tumor …

Deep learning (DL) models have received particular attention in medical imaging due to
their promising pattern recognition capabilities. However, Deep Neural Networks (DNNs) …

The Iris pattern is a unique biological feature for each individual, making it a valuable and
powerful tool for human identification. In this paper, an efficient framework for iris recognition …

Face recognition is one of the most popular techniques to achieve the goal of figuring out the
identity of a person. This study has been conducted to develop a new non-linear subspace …

Developing a computer-aided diagnosis (CAD) scheme to classify between malignant and
benign breast lesions can play an important role in improving MRI screening efficacy. This …

Methods: The present study aimed to apply the feature selection method based on the
binary bat algorithm (BBA) to increase the accuracy of the breast cancer diagnosis. Feature …