Mental illnesses, such as depression, are highly prevalent and have been shown to impact
an individual's physical health. Recently, artificial intelligence (AI) methods have been …

Automatic Leukemia or blood cancer detection is a challenging job and is very much
required in healthcare centers. It has a significant role in early diagnosis and treatment …

Long short-term memory (LSTM) neural networks and attention mechanism have been
widely used in sentiment representation learning and detection of texts. However, most of …

Recently, depression research has received considerable attention and there is an urgent
need for objective and validated methods to detect depression. Depression detection based …

In real-life communication, nonverbal vocalization such as laughter, cries or other emotion
interjections, within an utterance play an important role for emotion expression. In previous …

Background Bias-prone psychiatric interviews remain the mainstay of bipolar disorder (BD)
assessment. The development of digital phenotyping promises to improve BD management …

The aim of this paper is to investigate emotion recognition using a multimodal approach that
exploits convolutional neural networks (CNNs) with multiple input. Multimodal approaches …

As mental health (MH) disorders become increasingly prevalent, their multifaceted
symptoms and comorbidities with other conditions introduce complexity to diagnosis, posing …

Emotions can be expressed through multiple complementary modalities. This study selected
speech and facial expressions as modalities by which to recognize emotions. Current …

The need for objective measurement in psychiatry has stimulated interest in alternative
indicators of the presence and severity of illness. Speech may offer a source of information …