Emotion recognition is the ability to precisely infer human emotions from numerous sources
and modalities using questionnaires, physical signals, and physiological signals. Recently …

Mental disorders are rapidly increasing each year and have become a major challenge
affecting the social and financial well-being of individuals. There is a need for phenotypic …

Rapid technological advancements are altering people's communication styles. With the
growth of the Internet, social networks (Twitter, Facebook, Telegram, and Instagram) have …

Depression and bipolar disorder are mood disorders affecting millions of people worldwide
that can have severe impacts on one's quality of life. Our ability to detect these illnesses is …

A novel wearable consumer electronics device for detecting Major Depressive Disorder
(MDD) has been developed using deep learning techniques for smart healthcare. Accurate …

This paper explores the current machine learning based methods used to identify Attention
Deficit Hyperactivity Disorder (ADHD) and depression in humans. Prevalence of mental …

Depression is a major psychological disorder with a growing impact worldwide. Traditional
methods for detecting the risk of depression, predominantly reliant on psychiatric …

This paper aims to propose an automated and less complex machine learning-based
depression detection system DepML utilizing the IoMT framework in smart hospitals. This …

Depression is the most prevalent mental disorder in the world. One of the most adopted tools
for depression screening is the Beck Depression Inventory-II (BDI-II) questionnaire. Patients …

Mental illness has grown to become a prevalent and global health concern that affects
individuals across various demographics. Timely detection and accurate diagnosis of mental …