Psychiatry

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

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Automated Autism Assessment With Multimodal Data and Ensemble Learning: A Scalable and Consistent Robot-Enhanced Therapy Framework.

Navigating the complexities of Autism Spectrum Disorder (ASD) diagnosis and intervention requires a ...

Enhancing smart healthcare with female students' stress and anxiety detection using machine learning.

Machine learning (ML) is widely used to predict and detect stress and anxiety. Early detection of st...

Multivariate Classification of Adolescent Major Depressive Disorder Using Whole-brain Functional Connectivity.

RATIONALE AND OBJECTIVES: Adolescent major depressive disorder (MDD) is a serious mental health cond...

Association of the characteristics of brain magnetic resonance imaging with genes related to disease onset in schizophrenia patients.

BACKGROUND: Schizophrenia (SCH) is a complex neurodevelopmental disorder, whose pathogenesis is not ...

The interpretable machine learning model for depression associated with heavy metals via EMR mining method.

Limited research exists on the association between depression and heavy metal exposure. This study a...

Exploring the Potential of Large Language Models for Automated Safety Plan Scoring in Outpatient Mental Health Settings.

The Safety Planning Intervention (SPI) produces a plan to help manage patients' suicide risk. High-q...

Fall recognition using a three stream spatio temporal GCN model with adaptive feature aggregation.

The prevention of falls is paramount in modern healthcare, particularly for the elderly, as falls ca...

Recurrent and convolutional neural networks in classification of EEG signal for guided imagery and mental workload detection.

The Guided Imagery technique is reported to be used by therapists all over the world in order to inc...

The Future of the Psychiatrist.

OBJECTIVE: The American Psychiatric Association (APA) issued a 2023 report on the future of psychiat...

Nanopsychiatry: Advancing psychiatric diagnosis and monitoring through nanotechnology-based detection.

Nanopsychiatry, operating at the nanoscale, leverages engineered nanomaterials and nanodevices to re...

An Interpretable Model With Probabilistic Integrated Scoring for Mental Health Treatment Prediction: Design Study.

BACKGROUND: Machine learning (ML) systems in health care have the potential to enhance decision-maki...

Machine learning-driven development of a stratified CES-D screening system: optimizing depression assessment through adaptive item selection.

OBJECTIVE: To develop a stratified screening tool through machine learning approaches for the Center...

Who Tweets for the autistic community? A natural language processing-driven investigation.

The formation of autism advocacy organisations led by family members of autistic individuals led to ...

Hybrid CNN and random forest model with late fusion for detection of autism spectrum disorder in Toddlers.

Accurate and early diagnosis of Autism Spectrum Disorder (ASD) in toddlers is crucial for effective ...

The role of generative artificial intelligence in psychiatric education- a scoping review.

BACKGROUND: The growing prevalence of mental health conditions, worsened by the COVID-19 pandemic, h...

An ensemble approach using multidimensional convolutional neural networks in wavelet domain for schizophrenia classification from sMRI data.

Schizophrenia is a complicated mental condition marked by disruptions in thought processes, percepti...

Psychometric properties and Turkish adaptation of the artificial intelligence attitude scale (AIAS-4): evidence for construct validity.

Artificial intelligence (AI) attitude scales can be used to better evaluate the benefit and drawback...

Artificial Intelligence and Qualitative Analysis of Emergency Department Telemental Health Care Implementation Survey.

: Implementation of telemental health care in emergency departments (EDs) in the United States (U.S....

Perceived Barriers and Facilitators of Use of Artificial Intelligence in Eating Disorder Care: A Commentary on Linardon et al. (2025).

Artificial intelligence (AI) has the potential to revolutionize mental health care, including for ea...

Automated ADHD detection using dual-modal sensory data and machine learning.

This study explores using dual-modal sensory data and machine learning to objectively identify Atten...

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