AIMC Topic: Mental Health

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Transforming mental health research and care through artificial intelligence.

Science (New York, N.Y.)
Artificial intelligence (AI) holds transformative potential for the care of people with mental health illnesses. This Review explores key domains and emerging applications of AI in mental health, emphasizing the challenges that must be addressed to e...

Continuous Monitoring of Mental Health through Streaming Machine Learning with Counterfactual Explanations.

Journal of medical systems
Good mental health is crucial for well-being. Unfortunately, despite the advancements of automatic detection solutions in the mental health field, along with the existence of effective treatments, a large percentage of affected people receive no care...

Key personality and training factors influencing athletes' mental health - based on machine learning.

PloS one
Athletes face a higher risk of mental health disorders compared to the general population, and prior theoretical and empirical work suggests that personality traits and training-related factors may play important roles in shaping athletes' mental hea...

Generative AI Mental Health Chatbots as Therapeutic Tools: Systematic Review and Meta-Analysis of Their Role in Reducing Mental Health Issues.

Journal of medical Internet research
BACKGROUND: In recent years, artificial intelligence (AI) has driven the rapid development of AI mental health chatbots. Most current reviews investigated the effectiveness of rule-based or retrieval-based chatbots. To date, there is no comprehensive...

PERMA-guided multi-topology graph neural networks for cross-cultural student well-being prediction.

PloS one
Student well-being prediction is of great significance for promoting personalized education and preventing mental health problems, but existing methods suffer from limitations including lack of psychological theory guidance, neglect of student relati...

Income, psychological security, and subjective well-being in urban China: a machine learning analysis with SHAP interpretation.

BMC psychology
BACKGROUND: Subjective well-being has become a core indicator for measuring social progress and policy effectiveness. However, the "Easterlin Paradox" remains prevalent, and this paradox refers to the disconnect between economic growth and improvemen...

H3-MOSAIC: multimodal generative AI for semantic place detection from high-frequency GPS on H3 grids in mental health geomatics.

International journal of health geographics
BACKGROUND: Mental-health geomatics require reliable ways to convert high-frequency GPS trajectories into meaningful place types that support indicators such as homestay, location entropy, and spatial extent of daily activities. Raw coordinates are t...

From digital disruption to mental health: the impact of AI-induced educational anxiety on teacher well-being in the era of smart education.

BMC public health
BACKGROUND: In the context of artificial intelligence (AI) profoundly reshaping the educational ecosystem, teachers, as core drivers of the intelligent education era, are facing unprecedented opportunities and mental health challenges. Although AI de...

Relationship between cognitive abilities and mental health as represented by cognitive abilities at the neural and genetic levels of analysis.

eLife
Cognitive abilities are closely tied to mental health from early childhood. This study explores how neurobiological units of analysis of cognitive abilities-multimodal neuroimaging and polygenic scores (PGS)-represent this connection. Using data from...

From dry eye to depression: a machine learning-based framework for predicting adolescent mental health.

BMC medical informatics and decision making
BACKGROUND: Adolescent depression is a major public health concern. Physical health indicators are rarely included in risk tools. We examined whether adding dry eye disease (DED) to psychosocial and behavioral factors improves prediction of depressiv...