Abstract Purpose of Review Artificial intelligence (AI) technology holds both great promise to
transform mental healthcare and potential pitfalls. This article provides an overview of AI and …

Advances in computer science and data-analytic methods are driving a new era in mental
health research and application. Artificial intelligence (AI) technologies hold the potential to …

Depression is a common reason for an increase in suicide cases worldwide. Thus, to
mitigate the effects of depression, accurate diagnosis and treatment are needed. An …

Video anomaly detection is of critical practical importance to a variety of real applications
because it allows human attention to be focused on events that are likely to be of interest, in …

Electroencephalogram (EEG)-based major depressive disorder (MDD) machine learning
detection models can objectively differentiate MDD from healthy controls but are limited by …

Emotion recognition from Electroencephalography (EEG) is proved to be a good choice as it
cannot be mimicked like speech signals or facial expressions. EEG signals of emotions are …

Mental disorders represent critical public health challenges as they are leading contributors
to the global burden of disease and intensely influence social and financial welfare of …

Background Mental health problems, such as depression in children have far-reaching
negative effects on child, family and society as whole. It is necessary to identify the reasons …

According to the WHO, the number of mental disorder patients, especially depression
patients, has overgrown and become a leading contributor to the global burden of disease …

Electroencephalogram (EEG), boasting the advantages of portability, low cost, and
hightemporal resolution, is a non-invasive brain-imaging modality that can be used to …