Psychiatry

Designing Depression Screening Chatbots.

Advances in voice recognition, natural language processing, and artificial intelligence have led to the increasing availability and use of conversational agents (chatbots) in different settings. Chatbots are systems that mimic human dialogue interaction through text or voice. This paper describes a series of design considerations for integrating chatbots interfaces with health services. The presen...

Predicting Sex-Specific Nonfatal Suicide Attempt Risk Using Machine Learning and Data From Danish National Registries.

Suicide attempts are a leading cause of injury globally. Accurate prediction of suicide attempts might offer opportunities for prevention. This case-cohort study used machine learning to examine sex-specific risk profiles for suicide attempts in Danish nationwide registry data. Cases were all persons who made a nonfatal suicide attempt between 1995 and 2015 (n = 22,974); the subcohort was a 5% ran...

Deep learning model reveals potential risk genes for ADHD, especially Ephrin receptor gene EPHA5.

Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder. Although genome-wide association studies (GWAS) identify the ...

De novo generation of dual-target ligands using adversarial training and reinforcement learning.

Artificial intelligence, such as deep generative methods, represents a promising solution to de novo design of molecules with the desired properties. ...

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 invasive approaches, including robot-assisted PN (RAP...

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 factors between patients who underwent Da Vinci r...

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. However, the lack of interpretability of these algorith...

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 symmetrically weighted local binary patterns (SLBP)-based...

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 preliminary screening. The uncontrolled self-admini...

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 diagnosed using self-reported symptoms. This makes it ...

Optimizing Input for Gesture Recognition using Convolutional Networks on HD-sEMG Instantaneous Images.

Hand gesture recognition using high-density surface electromyography (HD-sEMG) has gained increasing attention recently due its advantages of high spa...

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 prognosis, possibly through links between obesity and brai...

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 contrast, individual differences in mental function...

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

INTRODUCTION: Robot-assisted Therapy (RAT) can improve the behavior of children with Autism Spectrum Disorder (ASD) in a spontaneous and entertaining ...

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 research field for the computer science and medical eng...

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 useful to understand the etiopathogenesis of autism ...

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 known that individuals show heterogeneous trajectori...

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-based classifier (MC) was developed to identify su...

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 evolution. The problem of deceptiveness caused by...

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 unlabeled data to improve the performance of the m...