Latest AI and machine learning research in psychiatry for healthcare professionals.
We propose TB-GCAN, a tri-branch cross-attention graph neural network for schizophrenia classification using multimodal MRI, including sMRI, fMRI, and DTI. Built on a multi-site dataset of 1191 samples from seven scanning sites, the model exploits atlas-defined one-to-one anatomical correspondence across modalities to enable node-level cross-attention during intermediate representation learning. I...
The rapid growth of tele-counseling and the use of lay counselors in high-volume, low-resource mental health services has created a need for scalable tools for early detection and triage. Effective personalization now requires stratifying individuals by dominant symptom profiles, such as appetite, agency, anxiety, and sleep disturbances. Depression symptoms vary widely, even among those with simil...
INTRODUCTION: As artificial intelligence (AI) becomes more common in healthcare, nursing students need to be both mentally and emotionally ready to us...
BACKGROUND: Differences in social media addiction, anxiety, and parenting self-efficacy according to maternal employment status have important implica...
This study aimed to develop and compare the performance of machine learning models in identifying depressive symptom status among middle-aged and elde...
As generative AI becomes a standard fixture in graduate education, the pedagogical challenge has shifted from detection to integration. This article d...
PURPOSE: Previous literature has identified multiple risk factors for anxiety among individuals with cancer. However, the relative importance across m...
BACKGROUND: Psychiatric disorders represent a major burden for patients with epilepsy (PwE). This study examined how demographic, epilepsy-related, an...
Social-affective changes are early indicators of psychosis relapse, yet their dynamic and subjective nature makes them difficult to capture between ro...
Conversational AI is increasingly being used by young people for emotional support, advice and conversations about personal concerns. Emerging evidenc...
BACKGROUND: Generative artificial intelligence (genAI) has the capacity to create realistic and convincing animal videos; however, it must simplify an...
Generative artificial intelligence can scale precision evidence-based psychotherapy.
BACKGROUND: Standard echocardiography reports use complex terminology, limiting patient comprehension and exacerbating preconsultation anxiety. Large ...
OBJECTIVE: We aimed to use machine learning (ML) models to investigate the impact of clinical, social and behavioural factors on 1-year progression fr...
BACKGROUND: Most applications for depression lack comprehensive theoretical integration and qualitative assessments of university students' needs rema...
BACKGROUND: Artificial intelligence (AI)-based nursing interventions are increasingly being used to manage chronic illnesses; however, their definitiv...
BACKGROUND AND PURPOSE: Microglia are central regulators of neuroinflammation in depression. Drivers involved remain incompletely understood. Sigma no...
Aluminum phosphide (AlP) is a chemical compound that is used as a pesticide for suicidal purposes and can cause death, and it poses a challenge to hea...
BACKGROUND: High-risk subsolid pulmonary nodules, especially mixed ground-glass nodules, can represent precancerous or early-stage lung adenocarcinoma...
This study integrates causal inference, graph analysis, temporal complexity measures, and machine learning to examine whether individual symptom traje...