Diabetes is a chronic disease that continues to be a significant and global concern since it
affects the entire population's health. It is a metabolic disorder that leads to high blood sugar …

This paper provides a comprehensive overview of the state-of-the-art in brain–computer
interfaces (BCI). It begins by providing an introduction to BCIs, describing their main …

The electroencephalogram (EEG) signals are a big data which are frequently corrupted by
motion artifacts. As human neural diseases, diagnosis and analysis need a robust …

The electroencephalography (EEG) signal is corrupted with some non-cerebral activities
due to patient movement during signal measurement. These non-cerebral activities are …

The use of machine learning algorithms for facial expression recognition and patient
monitoring is a growing area of research interest. In this study, we present a technique for …

Medical diagnosis is always a time and a sensitive approach to proper medical treatment.
Automation systems have been developed to improve these issues. In the process of …

Due to the increasing number of medical imaging images being utilized for the diagnosis
and treatment of diseases, lossy or improper image compression has become more …

In experimental analysis and computer‐aided design sustain scheme, segmentation of cell
liver and hepatic lesions by an automated method is a significant step for studying the …

Cancer is one of the top causes of mortality, and it arises when cells in the body grow
abnormally, like in the case of breast cancer. For people all around the world, it has now …

To better understand human brain dynamics during visually guided locomotion, we
developed a method of removing motion artifacts from mobile electroencephalography …