In light of the National Institute of Mental Health (NIMH)'s Research Domain Criteria (RDoC),
the advent of functional neuroimaging, novel technologies and methods provide new …

This paper discusses the promising areas of research into machine learning applications for
the prevention and correction of neurodegenerative and depressive disorders. These two …

Drowsiness detection (DD) has become a relevant area of active research in biomedical
signal processing. Recently, various deep learning (DL) researches based on the EEG …

Abstract The number of Major Depressive Disorder (MDD) patients is rising rapidly these
days following the incidence of COVID‐19 pandemic. It is challenging to detect MDD …

Depression is the most common mental illness, which has become the major cause of fear
and suicidal mortality or tendencies. Currently, about 10% of the world population has been …

Depression is one of the significant contributors to the global burden disease, affecting
nearly 264 million people worldwide along with the increasing rate of suicidal deaths …

Background Severe psychiatric disorders, including depressive disorders, schizophrenia
spectrum disorders, and intellectual disability, have devastating impacts on vital life domains …

Depression is considered by WHO as the main contributor to global disability and it poses
dangerous threats to approximately all aspects of human life, in particular public and private …

In recent medical research, tremendous progress has been made in the application of deep
learning (DL) techniques. This article systematically reviews how DL techniques have been …

Background In this modern era, depression is one of the most prevalent mental disorders
from which millions of individuals are affected today. The symptoms of depression are …