Psychiatry

Multi-modal deep learning of functional and structural neuroimaging and genomic data to predict mental illness.

Neuropsychiatric disorders such as schizophrenia are very heterogeneous in nature and typically diag...

Deep 3D-CNN for Depression Diagnosis with Facial Video Recording of Self-Rating Depression Scale Questionnaire.

The Self-Rating Depression Scale (SDS) questionnaire is commonly utilized for effective depression p...

Schizophrenia Detection in Adolescents from EEG Signals using Symmetrically weighted Local Binary Patterns.

Schizophrenia is one of the most complex of all mental diseases. In this paper, we propose a symmetr...

Interpretable SincNet-based Deep Learning for Emotion Recognition from EEG brain activity.

Machine learning methods, such as deep learning, show promising results in the medical domain. Howev...

The quantification and clinical analysis of depression and anxiety in patients undergoing Da Vinci robot-assisted radical gastrectomy and open radical gastrectomy.

The purpose of paper is to investigate the depression and anxiety as well as independent influential...

Health-Related Quality of Life in Patients with Small Renal Mass Who Underwent Robot-Assisted Partial Nephrectomy: A Prospective Evaluation.

There have been insufficient data regarding the impact of partial nephrectomy (PN) with minimal inv...

Obesity as a Risk Factor for Accelerated Brain Ageing in First-Episode Psychosis-A Longitudinal Study.

BACKGROUND: Obesity is highly prevalent in schizophrenia, with implications for psychiatric prognosi...

Population modeling with machine learning can enhance measures of mental health.

BACKGROUND: Biological aging is revealed by physical measures, e.g., DNA probes or brain scans. In c...

[Therapeutic use of robotics in children with Autism Spectrum Disorder].

INTRODUCTION: Robot-assisted Therapy (RAT) can improve the behavior of children with Autism Spectrum...

A 3D multiscale view convolutional neural network with attention for mental disease diagnosis on MRI images.

Computer Assisted Diagnosis (CAD) based on brain Magnetic Resonance Imaging (MRI) is a popular resea...

Taming the chaos?! Using eXplainable Artificial Intelligence (XAI) to tackle the complexity in mental health research.

Discriminating Heterogeneous Trajectories of Resilience and Depression After Major Life Stressors Using Polygenic Scores.

IMPORTANCE: Major life stressors, such as loss and trauma, increase the risk of depression. It is kn...

Brief Report: Neuroimaging Endophenotypes of Social Robotic Applications in Autism Spectrum Disorder.

A plethora of neuroimaging studies have focused on the discovery of potential neuroendophenotypes us...

Accelerated Aging of the Amygdala in Alcohol Use Disorders: Relevance to the Dark Side of Addiction.

Here we assessed changes in subcortical volumes in alcohol use disorder (AUD). A simple morphometry-...

Probabilistic Contextual and Structural Dependencies Learning in Grammar-Based Genetic Programming.

Genetic Programming is a method to automatically create computer programs based on the principles of...

Semi-supervised random forest regression model based on co-training and grouping with information entropy for evaluation of depression symptoms severity.

Semi-supervised learning has always been a hot topic in machine learning. It uses a large number of ...

Future perspectives of robot psychiatry: can communication robots assist psychiatric evaluation in the COVID-19 pandemic era?

PURPOSE OF REVIEW: Direct face-to-face interview between a psychiatrist and a patient is crucial in ...

Robot-induced hallucinations in Parkinson's disease depend on altered sensorimotor processing in fronto-temporal network.

Hallucinations in Parkinson's disease (PD) are disturbing and frequent non-motor symptoms and consti...

Research on the influence of attention and emotion of tea drinkers based on artificial neural network.

Tea can help to regulate the mood of human. Based on the influence of tea on people's mood and atten...

Identification of Suicide Attempt Risk Factors in a National US Survey Using Machine Learning.

IMPORTANCE: Because more than one-third of people making nonfatal suicide attempts do not receive me...

Using Natural Language Processing on Electronic Health Records to Enhance Detection and Prediction of Psychosis Risk.

BACKGROUND: Using novel data mining methods such as natural language processing (NLP) on electronic ...