For years, the scientific community has researched monitoring approaches for the detection
of certain mental disorders and risky behaviors, like depression, eating disorders, gambling …

Depression has robust natural language correlates and can increasingly be measured in
language using predictive models. However, despite evidence that language use varies as …

As a common psychological disorder, depression is generally detected based on scales and
interviews, which are often affected by subjective or environmental factors. In order to assist …

We propose a simple approach for weighting self-connecting edges in a Graph
Convolutional Network (GCN) and show its impact on depression detection from transcribed …

Mental health challenges pose considerable global burdens on individuals and
communities. Recent data indicates that more than 20% of adults may encounter at least …

Early diagnosis of psychological disorders is very important for patients to regain their
health. Research shows that many patients do not realize that they have a psychological …

Depression is a serious mental illness that affects millions worldwide and consequently has
attracted considerable research interest in recent years. Within the field of automated …

Massive social media data can reflect people's authentic thoughts, emotions,
communication, etc., and therefore can be analyzed for early detection of mental health …

We employ a Large Language Model (LLM) to convert unstructured psychological interviews
into structured questionnaires spanning various psychiatric and personality domains. The …

This paper explores the impact of incorporating sentiment, emotion, and domain-specific
lexicons into a transformer-based model for depression symptom estimation. Lexicon …