Psychiatry

Latest AI and machine learning research in psychiatry for healthcare professionals.

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Video-audio neural network ensemble for comprehensive screening of autism spectrum disorder in young children.

A timely diagnosis of autism is paramount to allow early therapeutic intervention in preschoolers. D...

Exploring key factors influencing depressive symptoms among middle-aged and elderly adult population: A machine learning-based method.

OBJECTIVE: This paper aims to investigate the key factors, including demographics, socioeconomics, p...

Using machine learning modeling to identify childhood abuse victims on the basis of personality inventory responses.

Trauma is very common and associated with significant co-morbidity world-wide, particularly PTSD and...

Detection of Low Resilience Using Data-Driven Effective Connectivity Measures.

Conventional thresholding techniques for graph theory analysis, such as absolute, proportional and m...

Classification of psychosis spectrum disorders using graph convolutional networks with structurally constrained functional connectomes.

This article considers the problem of classifying individuals in a dataset of diverse psychosis spec...

Fast, variable stiffness-induced braided coiled artificial muscles.

Biomimetic actuation technologies with high muscle strokes, cycle rates, and work capacities are nec...

Potential promises and perils of artificial intelligence in psychotherapy -The AI Psychotherapist (APT).

OBJECTIVE: Since the release of ChatGPT, popular demand has driven the use of social chatbots as pse...

Machine learning for anxiety and depression profiling and risk assessment in the aftermath of an emergency.

BACKGROUND & OBJECTIVES: Mental health disorders pose an increasing public health challenge worsened...

Identifying the most critical side effects of antidepressant drugs: a new model proposal with quantum spherical fuzzy M-SWARA and DEMATEL techniques.

Identifying and managing the most critical side effects encourages patients to take medications regu...

Creating a diagnostic assessment model for autism spectrum disorder by differentiating lexicogrammatical choices through machine learning.

This study explores the challenge of differentiating autism spectrum (AS) from non-AS conditions in ...

Identification of Bipolar Disorder and Schizophrenia Based on Brain CT and Deep Learning Methods.

With the increasing prevalence of mental illness, accurate clinical diagnosis of mental illness is c...

Relationship matters: Using machine learning methods to predict the mental health severity of Chinese college freshmen during the pandemic period.

BACKGROUND: Pandemics act as stressors and may lead to frequent mental health disorders. College stu...

The Impact of Medical Explainable Artificial Intelligence on Nurses' Innovation Behaviour: A Structural Equation Modelling Approach.

This study aims to investigate the influence of medical explainable artificial intelligence (XAI) o...

MRI-based deep learning for differentiating between bipolar and major depressive disorders.

Mood disorders, particularly bipolar disorder (BD) and major depressive disorder (MDD), manifest cha...

Using Natural Language Processing to develop risk-tier specific suicide prediction models for Veterans Affairs patients.

Suicide is a leading cause of death. Suicide rates are particularly elevated among Department of Vet...

Artificial intelligence and forensic mental health in Africa: a narrative review.

This narrative review examines the integration of Artificial Intelligence (AI) tools into forensic p...

Artificial intelligence and psychedelic medicine.

Artificial intelligence (AI) and psychedelic medicines are among the most high-profile evolving disr...

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