Psychiatry

A systematic review of structural neuroimaging markers of psychotherapeutic and pharmacological treatment for obsessive-compulsive disorder.

Identifying individual difference factors associated with treatment response and putative mechanisms of therapeutic change may improve treatment for Obsessive Compulsive Disorder (OCD). Our systematic review of structural neuroimaging markers (i.e., morphometry, structural connectivity) of psychotherapy and medication treatment response for OCD identified 26 eligible publications from 20 studies (...

Efficacy and effectiveness of therapist-guided internet versus face-to-face cognitive behavioural therapy for depression via counterfactual inference using naturalistic registers and machine learning in Finland: a retrospective cohort study.

BACKGROUND: According to meta-analyses of randomised controlled trials (RCTs), therapist-guided internet-delivered cognitive behavioural therapy (iCBT) is as effective a treatment for depression as traditional face-to-face CBT (fCBT), despite its substantially lower costs. However, RCTs are not always representative of routine practice, which could inflate effectiveness estimates. We combined rich...

Identifying Adolescent Depression and Anxiety Through Real-World Data and Social Determinants of Health: Machine Learning Model Development and Validation.

BACKGROUND: The prevalence of adolescent mental health conditions such as depression and anxiety has significantly increased. Despite the potential of...

Apriori algorithm based prediction of students' mental health risks in the context of artificial intelligence.

INTRODUCTION: The increasing prevalence of mental health challenges among college students necessitates innovative approaches to early identification ...

A novel framework to predict ADHD symptoms using irritability in adolescents and young adults with and without ADHD.

BACKGROUND: Attention Deficit Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder in children and adolescents characterized by persi...

Differentiating Functional Connectivity Patterns in ADHD and Autism Among the Young People: A Machine Learning Solution.

OBJECTIVE: ADHD and autism are complex and frequently co-occurring neurodevelopmental conditions with shared etiological and pathophysiological elemen...

Physician Perspectives on the Potential Benefits and Risks of Applying Artificial Intelligence in Psychiatric Medicine: Qualitative Study.

BACKGROUND: As artificial intelligence (AI) tools are integrated more widely in psychiatric medicine, it is important to consider the impact these too...

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

AIMS: The way that individuals subjectively experience the world greatly influences their own mental well-being. However, it remains a considerable ch...

Analyzing patterns of frequent mental distress in Alzheimer's patients: A generative AI approach.

This study tackles creating Python code for beginners with generative AI and analyzing trends in mental distress among Alzheimer's patients in the US ...

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

OBJECTIVE: Artificial intelligence (AI) becomes increasingly integrated into the workplace, its associated job substitution risks for employees are mo...

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

BACKGROUND: Early maladaptive schemas (EMSs) are pervasive, self-defeating patterns of thoughts and emotions underlying most mental health problems an...

The Efficacy of Conversational AI in Rectifying the Theory-of-Mind and Autonomy Biases: Comparative Analysis.

BACKGROUND: The increasing deployment of conversational artificial intelligence (AI) in mental health interventions necessitates an evaluation of thei...

Genome data based deep learning identified new genes predicting pharmacological treatment response of attention deficit hyperactivity disorder.

Although the efficacy of pharmacy in the treatment of attention deficit/hyperactivity disorder (ADHD) has been well established, the lack of predictor...

Does the Digital Therapeutic Alliance Exist? Integrative Review.

BACKGROUND: Mental health disorders significantly impact global populations, prompting the rise of digital mental health interventions, such as artifi...

Artificial intelligence in mental health care: a systematic review of diagnosis, monitoring, and intervention applications.

Artificial intelligence (AI) has been recently applied to different mental health illnesses and healthcare domains. This systematic review presents th...

Knowledge Distillation Guided Interpretable Brain Subgraph Neural Networks for Brain Disorder Exploration.

The human brain is a highly complex neurological system that has been the subject of continuous exploration by scientists. With the help of modern neu...

Larger models yield better results? Streamlined severity classification of ADHD-related concerns using BERT-based knowledge distillation.

This work focuses on the efficiency of the knowledge distillation approach in generating a lightweight yet powerful BERT-based model for natural langu...

Predictors of depression among Chinese college students: a machine learning approach.

BACKGROUND: Depression is highly prevalent among college students, posing a significant public health challenge. Identifying key predictors of depress...

Lurasidone uses and dosages in Spain: RETROLUR, a real-world retrospective analysis using artificial intelligence.

INTRODUCTION: Lurasidone is used for schizophrenia and bipolar depression in many countries, yet there is a lack of existing literature about its use,...

Emotional stimulated speech-based assisted early diagnosis of depressive disorders using personality-enhanced deep learning.

BACKGROUND: Early diagnosis of depression is crucial, and speech-based early diagnosis of depression is promising, but insufficient data and lack of t...