In machine learning, two approaches outperform traditional algorithms: ensemble learning
and deep learning. The former refers to methods that integrate multiple base models in the …

Deep learning (DL) is revolutionizing evidence-based decision-making techniques that can
be applied across various sectors. Specifically, it possesses the ability to utilize two or more …

Alzheimer's disease (AD) is a progressive and irreversible brain degenerative disorder. Mild
cognitive impairment (MCI) is a clinical precursor of AD. Although some treatments can …

Coronavirus disease (COVID‐19) is a viral infection caused by SARS‐CoV‐2. The
modalities such as computed tomography (CT) have been successfully utilized for the early …

Numerous machine learning (ML) approaches have been proposed for automatic
classification of Alzheimer's disease (AD) from brain imaging data. In particular, over 30 …

Alzheimer's disease is an incurable neurodegenerative disease primarily affecting the
elderly population. Efficient automated techniques are needed for early diagnosis of …

An encephalogram (EEG) is a commonly used ancillary test to aide in the diagnosis of
epilepsy. The EEG signal contains information about the electrical activity of the brain …

Alzheimer's disease (AD) is one of the most common form of dementia which mostly affects
elderly people. AD identification in early stages is a difficult task in medical practice and …

Alzheimer's Disease (AD) is one of the leading causes of death in developed countries.
From a research point of view, impressive results have been reported using computer-aided …

Deep learning algorithms, in particular convolutional networks, have rapidly become a
methodology of choice for analyzing medical images. This paper reviews the major deep …