Neuropsychiatric disorders pose a high societal cost, but their treatment is hindered by lack
of objective outcomes and fidelity metrics. AI technologies and specifically Natural …

Psychological health, ie, citizens' emotional and mental well-being, is one of the most
neglected public health issues. Depression is the most common mental health issue and the …

The importance and pervasiveness of emotions in our lives makes affective computing a
tremendously important and vibrant line of work. Systems for automatic emotion recognition …

Online social networks can be used for mental healthcare monitoring using Artificial
Intelligence and Machine Learning techniques for detecting various mental health disorders …

In this narrative review, we survey recent empirical evaluations of AI-based language
assessments and present a case for the technology of large language models to be poised …

We provide an overview of the CLPsych 2022 Shared Task, which focusses on the
automatic identification of 'Moments of Change'in lon-gitudinal posts by individuals on social …

We propose a deep learning architecture and test three other machine learning models to
automatically detect individuals that will attempt suicide within (1) 30 days and (2) six …

Many NLG tasks such as summarization, dialogue response, or open domain question
answering focus primarily on a source text in order to generate a target response. This …

Mental disorders and suicide are considered global health problems faced by many
countries worldwide. Even though advancements have been made to improve mental …

Overfitting is a common issue in machine learning-based depression detection model.
Overfitting occurs when a machine learning model uses garbage data in the training …