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Mental Health

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Mental health phenotypes of well-controlled HIV in Uganda.

Frontiers in public health
INTRODUCTION: The phenotypic expression of mental health (MH) conditions among people with HIV (PWH) in Uganda and worldwide are heterogeneous. Accordingly, there has been a shift toward identifying MH phenotypes using data-driven methods capable of ...

Improving unified information extraction in Chinese mental health domain with instruction-tuned LLMs and type-verification component.

Artificial intelligence in medicine
BACKGROUND: Extracting psychological counseling help-seeker information from unstructured text is crucial for providing effective mental health support. This task involves identifying personal emotions, psychological states, and underlying psychologi...

Fast, smart, and adaptive: using machine learning to optimize mental health assessment and monitor change over time.

Scientific reports
In mental health, accurate symptom assessment and precise measurement of patient conditions are crucial for clinical decision-making and effective treatment planning. Traditional assessment methods can be burdensome, especially for vulnerable populat...

Utilizing natural language processing for precision prevention of mental health disorders among youth: A systematic review.

Computers in biology and medicine
BACKGROUND: The global mental health crisis has created barriers to youth mental healthcare, leaving many disorders unaddressed. Precision prevention, which identifies individual risks, offers the potential for tailored interventions. While natural l...

Artificial Intelligence Job Substitution Risks, Digital Self-efficacy, and Mental Health Among Employees.

Journal of occupational and environmental medicine
OBJECTIVE: Artificial intelligence (AI) becomes increasingly integrated into the workplace, its associated job substitution risks for employees are more evident, resulting in significant repercussions for their well-being. This study tries to elucida...

Co-Designing an Electronic Health Record Derived Digital Dashboard to Support Fair-AI Applications in Mental Health.

Studies in health technology and informatics
Guided by interviews with end-users and in collaboration with lived-experience advisors, the Fairness Dashboard is being co-designed to promote the standardized and responsible utilization of sociodemographic data in statistical and machine learning ...

Predicting mental health disparities using machine learning for African Americans in Southeastern Virginia.

Scientific reports
This study examined mental health disparities among African Americans using AI and machine learning for outcome prediction. Analyzing data from African American adults (18-85) in Southeastern Virginia (2016-2020), we found Mood Affective Disorders we...

The application of artificial intelligence in the field of mental health: a systematic review.

BMC psychiatry
INTRODUCTION: The integration of artificial intelligence in mental health care represents a transformative shift in the identification, treatment, and management of mental disorders. This systematic review explores the diverse applications of artific...

Towards a latent space cartography of subjective experience in mental health.

Psychiatry and clinical neurosciences
AIMS: The way that individuals subjectively experience the world greatly influences their own mental well-being. However, it remains a considerable challenge to precisely characterize the breadth and depth of such experiences. One persistent problem ...

Unraveling Online Mental Health Through the Lens of Early Maladaptive Schemas: AI-Enabled Content Analysis of Online Mental Health Communities.

Journal of medical Internet research
BACKGROUND: Early maladaptive schemas (EMSs) are pervasive, self-defeating patterns of thoughts and emotions underlying most mental health problems and are central in schema therapy. However, the characteristics of EMSs vary across demographics, and ...