Psychiatry

Will artificial intelligence eventually replace psychiatrists?

The dystopian scenario of an 'artificial intelligence takeover' imagines artificial intelligence (AI...

Machine Learning to Differentiate Risk of Suicide Attempt and Self-harm After General Medical Hospitalization of Women With Mental Illness.

BACKGROUND: Suicide prevention is a public health priority, but risk factors for suicide after medic...

Multimodal Machine Learning Workflows for Prediction of Psychosis in Patients With Clinical High-Risk Syndromes and Recent-Onset Depression.

IMPORTANCE: Diverse models have been developed to predict psychosis in patients with clinical high-r...

LEGAL AND PRACTICAL PROBLEMS OF USE OF ARTIFICIAL INTELLIGENCE-BASED ROBOTS IN FORENSIC PSYCHIATRY.

OBJECTIVE: The aim: This research aims to analyze the possibilities of using artificial intelligence...

[Ethics of (big) data applications in psychiatric practice].

BACKGROUND: Due to rapid digitalization, an increasing amount of data is available in healthcare set...

AI, Virtual Reality, and Robots Advancing Autism Diagnosis and Therapy.

Autism spectrum disorder (ASD) is a challenge in multiple ways. Just getting diagnosed can take mont...

Artificial intelligence: A rapid case for advancement in the personalization of Gynaecology/Obstetric and Mental Health care.

To evaluate and holistically treat the mental health sequelae and potential psychiatric comorbiditie...

[Patient-tailored approach in tertiary care expert centres using individual dynamic network analysis].

BACKGROUND: Patients with mental health disorders often have difficulty perceiving associations betw...

Machine learning: A primer for psychotherapy researchers.

Applied natural language processing in mental health big data.

Biologically plausible models of neural dynamics for rapid-acting antidepressant interventions.

Brief Report: Can a Composite Heart Rate Variability Biomarker Shed New Insights About Autism Spectrum Disorder in School-Aged Children?

Several studies show altered heart rate variability (HRV) in autism spectrum disorder (ASD), but fin...

[Study on classification and identification of depressed patients and healthy people among adolescents based on optimization of brain characteristics of network].

To enhance the accuracy of computer-aided diagnosis of adolescent depression based on electroencepha...

Machine Learning Analysis of Blood microRNA Data in Major Depression: A Case-Control Study for Biomarker Discovery.

BACKGROUND: There is a lack of reliable biomarkers for major depressive disorder (MDD) in clinical p...

Detecting and Classifying Self-injurious Behavior in Autism Spectrum Disorder Using Machine Learning Techniques.

Traditional self-injurious behavior (SIB) management can place compliance demands on the caregiver a...

[Effects of acupuncture on Nod-like receptor protein 3 inflammasome signal pathway in the prefrontal cortex of rat with depression].

OBJECTIVE: To observe the influence of acupuncture on the expression of pivotal molecules of Nod-lik...

Automated Detection of Enhanced DBS Device Settings.

Continuous deep brain stimulation (DBS) of the ventral striatum (VS) is an effective treatment for s...

Depression Severity Assessment for Adolescents at High Risk of Mental Disorders.

Recent progress in artificial intelligence has led to the development of automatic behavioral marker...

AI enabled suicide prediction tools: a qualitative narrative review.

Suicide poses a significant health burden worldwide. In many cases, people at risk of suicide do no...

Computational framework for detection of subtypes of neuropsychiatric disorders based on DTI-derived anatomical connectivity.

Many brain disorders - such as Alzheimer's disease, Parkinson's disease, schizophrenia and autism - ...

Large-Scale Structural Covariance Networks Predict Age in Middle-to-Late Adulthood: A Novel Brain Aging Biomarker.

The aging process is accompanied by changes in the brain's cortex at many levels. There is growing i...