Psychiatry

A case of fatal multidrug intoxication involving flualprazolam: distribution in body fluids and solid tissues.

PURPOSE: Designer benzodiazepines (DBZDs) increasingly emerged on the novel psychoactive substance (NPS) market in the last few years. They are usually sold as readily available alternatives to prescription benzodiazepines (BZDs) or added to counterfeit medicines. BZDs are generally considered relatively safe drugs due to the low risk of serious acute adverse effects in mono-intoxication, though e...

Retrospective Concomitant Nonrandomized Comparison of "Touch" Cautery Versus Athermal Dissection of the Prostatic Vascular Pedicles and Neurovascular Bundles During Robot-assisted Radical Prostatectomy.

BACKGROUND: During robotic-assisted radical prostatectomy (RARP), the use of electrocautery near the neurovascular bundles (NVBs) frequently results in thermal injury to the cavernous nerves. The cut and "touch" monopolar cautery technique has been suggested to reduce desiccating thermal injury caused by bipolar energy when vessels are sealed.

Deep graph neural network-based prediction of acute suicidal ideation in young adults.

Precise remote evaluation of both suicide risk and psychiatric disorders is critical for suicide prevention as well as for psychiatric well-being. Usi...

Design and Analysis of a Novel Integral Recurrent Neural Network for Solving Time-Varying Sylvester Equation.

To solve a general time-varying Sylvester equation, a novel integral recurrent neural network (IRNN) is designed and analyzed. This kind of recurrent ...

Sch-net: a deep learning architecture for automatic detection of schizophrenia.

BACKGROUND: Schizophrenia is a chronic and severe mental disease, which largely influences the daily life and work of patients. Clinically, schizophre...

Machine learning as the new approach in understanding biomarkers of suicidal behavior.

In psychiatry, compared to other medical fields, the identification of biological markers that would complement current clinical interview, and enable...

Affective Communication for Socially Assistive Robots (SARs) for Children with Autism Spectrum Disorder: A Systematic Review.

Research on affective communication for socially assistive robots has been conducted to enable physical robots to perceive, express, and respond emoti...

Improving the predictive potential of diffusion MRI in schizophrenia using normative models-Towards subject-level classification.

Diffusion MRI studies consistently report group differences in white matter between individuals diagnosed with schizophrenia and healthy controls. Nev...

Predicting pain among female survivors of recent interpersonal violence: A proof-of-concept machine-learning approach.

Interpersonal violence (IPV) is highly prevalent in the United States and is a major public health problem. The emergence and/or worsening of chronic ...

Explainable deep learning predictions for illness risk of mental disorders in Nanjing, China.

Epidemiological studies have revealed the associations of air pollutants and meteorological factors with a range of mental health conditions. However,...

Detecting suicidal risk using MMPI-2 based on machine learning algorithm.

Minnesota Multiphasic Personality Inventory-2 (MMPI-2) is a widely used tool for early detection of psychological maladjustment and assessing the leve...

Explaining distortions in metacognition with an attractor network model of decision uncertainty.

Metacognition is the ability to reflect on, and evaluate, our cognition and behaviour. Distortions in metacognition are common in mental health disord...

Evaluation of Effect of Curcumin on Psychological State of Patients with Pulmonary Hypertension by Magnetic Resonance Image under Deep Learning.

This research aimed to evaluate the right ventricular segmentation ability of magnetic resonance imaging (MRI) images based on deep learning and evalu...

Understanding terror states of online users in the context of COVID-19: An application of Terror Management Theory.

The COVID-19 pandemic has provided psych challenges for many in society. One such challenge is the anxiety that is created in many people faced with t...

Electrocardiogram-Based Emotion Recognition Systems and Their Applications in Healthcare-A Review.

Affective computing is a field of study that integrates human affects and emotions with artificial intelligence into systems or devices. A system or d...

Predicting subclinical psychotic-like experiences on a continuum using machine learning.

Previous studies applying machine learning methods to psychosis have primarily been concerned with the binary classification of chronic schizophrenia ...

Exploring perceptions of healthcare technologies enabled by artificial intelligence: an online, scenario-based survey.

BACKGROUND: Healthcare is expected to increasingly integrate technologies enabled by artificial intelligence (AI) into patient care. Understanding per...

Exploring Factors for Predicting Anxiety Disorders of the Elderly Living Alone in South Korea Using Interpretable Machine Learning: A Population-Based Study.

This epidemiological study aimed to develop an X-AI that could explain groups with a high anxiety disorder risk in old age. To achieve this objective,...

Face-Based Attention Recognition Model for Children with Autism Spectrum Disorder.

UNLABELLED: Attention recognition plays a vital role in providing learning support for children with autism spectrum disorders (ASD). The unobtrusiven...

Automatic classification of autism spectrum disorder in children using cortical thickness and support vector machine.

OBJECTIVE: Autism spectrum disorder (ASD) is a neurodevelopmental condition with a heterogeneous phenotype. The role of biomarkers in ASD diagnosis ha...