Social media is now being used to model mental well-being, and for understanding health
outcomes. Computer scientists are now using quantitative techniques to predict the …

Advances in large language models (LLMs) have empowered a variety of applications.
However, there is still a significant gap in research when it comes to understanding and …

Background The study of depression and anxiety using publicly available social media data
is a research activity that has grown considerably over the past decade. The discussion …

Background The COVID-19 pandemic is impacting mental health, but it is not clear how
people with different types of mental health problems were differentially impacted as the …

Users of social media often share their feelings or emotional states through their posts. In
this study, we developed a deep learning model to identify a user's mental state based on …

Depression is a kind of emotion that negatively impacts people's daily lives. The number of
people suffering from long-term feelings is increasing every year across the globe …

Mental disorders can severely affect quality of life, constitute a major predictive factor of
suicide, and are usually underdiagnosed and undertreated. Early detection of signs of …

Detection at an early stage is vital for the diagnosis of the majority of critical illnesses and is
the same for identifying people suffering from depression. Nowadays, a number of …

" Human-centered machine learning"(HCML) combines human insights and domain
expertise with data-driven predictions to answer societal questions. This area's inherent …

Powered by machine learning techniques, social media provides an unobtrusive lens into
individual behaviors, emotions, and psychological states. Recent research has successfully …