Analyzing texts such as open-ended responses, headlines, or social media posts is a time- and labor-intensive process highly susceptible to bias. However, large language models (LLMs) are promising to...

npj Digital Medicine - Language-based detection of depression with machine learning: systematic review and meta-analysis

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Translational Psychiatry - Global, regional, and national burden of mental disorders among adolescents and young adults, 1990–2021: a systematic analysis for the Global Burden of Disease...

Mental health services struggle to keep up with growing demand. This study explores how a RoBERTa large language model can help by analyzing text for signs of anxiety or depression. It uses online the...

Early detection of depression is critical for timely intervention. Natural language processing (NLP) and machine learning (ML) approaches have increasingly been used to automatically detect depression...

The ubiquity of smartphones and the rapid advance and widespread public adoption of “AI” tools like ChatGPT (especially among the young) have raised hopes among some researchers that such technologies...

Background: Ecological momentary assessment (EMA) is increasingly being incorporated into intervention studies to acquire a more fine-grained and ecologically valid assessment of change. The added uti...

Letter to the Editor

Using longitudinal survey and neuroimaging data from more than 11,000 adolescents in the United States, a machine learning model shows promising performance in identifying individuals at greater risk ...