Psychiatry

Deep Learning-Based Mental Health Model on Primary and Secondary School Students' Quality Cultivation.

The purpose was to timely identify the mental disorders (MDs) of students receiving primary and secondary education (PSE) (PSE students) and improve their mental quality. Firstly, this work analyzes the research status of the mental health model (MHM) and the main contents of PSE student-oriented mental health quality cultivation under deep learning (DL). Secondly, an MHM is implemented based on b...

Two stream Non-Local CNN-LSTM network for the auxiliary assessment of mental retardation.

At present, the assessment of mental retardation is mainly based on clinical interview, which requires the participation of experienced psychiatrist and is laborious. Studies have shown that there are correlations between mental retardation and abnormal behaviors (such as, hyperkinetic, tics, stereotypes, etc.). On the basis of this fact, a two stream Non-Local CNN-LSTM network has been proposed t...

DAC Stacking: A Deep Learning Ensemble to Classify Anxiety, Depression, and Their Comorbidity From Reddit Texts.

Depression is the most incapacitating disease worldwide, and it has an alarming comorbidity rate with anxiety. The use of social networks to expose pe...

Deep learning-based integration of genetics with registry data for stratification of schizophrenia and depression.

Currently, psychiatric diagnoses are, in contrast to most other medical fields, based on subjective symptoms and observable signs and call for new and...

Influence of Artificial Intelligence in Education on Adolescents' Social Adaptability: A Machine Learning Study.

This study aimed to investigate the influence of artificial intelligence in education (AIEd) on adolescents' social adaptability, as well as to identi...

Social robots in the instruction of social skills in autism: a comprehensive descriptive analysis of single-case experimental designs.

PURPOSE: The rapid technological advances, the traits of individuals with ASD and their interest in technology are promising for the instruction of so...

What can we learn about the psychiatric diagnostic categories by analysing patients' lived experiences with Machine-Learning?

BACKGROUND: To deliver appropriate mental healthcare interventions and support, it is imperative to be able to distinguish one person from the other. ...

A Machine Learning Approach for Predicting Non-Suicidal Self-Injury in Young Adults.

Artificial intelligence techniques were explored to assess the ability to anticipate self-harming behaviour in the mental health context using a datab...

A novel machine learning approach to shorten depression risk assessment for convenient uses.

BACKGROUND: Depression is a mental disorder affecting many people worldwide which has been exacerbated by the current pandemic. There is an urgent nee...

Exploring Characteristics of Homicide Offenders With Schizophrenia Spectrum Disorders Via Machine Learning.

The link between schizophrenia and homicide has long been the subject of research with significant impact on mental health policy, clinical practice, ...

Restorative rehabilitation robotics to promote function, independence and dignity: users' perspectives on clinical applications.

People with mobility impairments have reported that improving their walking is one of the most important goals of their rehabilitation. Novel robotic ...

The use of social robots with children and young people on the autism spectrum: A systematic review and meta-analysis.

BACKGROUND: Robot-mediated interventions show promise in supporting the development of children on the autism spectrum.

Information extraction from free text for aiding transdiagnostic psychiatry: constructing NLP pipelines tailored to clinicians' needs.

BACKGROUND: Developing predictive models for precision psychiatry is challenging because of unavailability of the necessary data: extracting useful in...

Perception Exploration on Robustness Syndromes With Pre-processing Entities Using Machine Learning Algorithm.

The majority of the current-generation individuals all around the world are dealing with a variety of health-related issues. The most common cause of ...

Monitoring and Analysis of Youth Sports Physique by Intelligent Medical Robot Based on Cognitive Computing.

As a key part of promoting the physical health of the people and promoting social progress, sports has ushered in comprehensive vitality. More and mor...

The Design of Psychological Education Intervention System in Universities Based on Deep Learning.

With the rapid development of Chinese society and economy as well as the deepening of the reform of the higher education management system and the cha...

Contrastive machine learning reveals the structure of neuroanatomical variation within autism.

Autism spectrum disorder (ASD) is highly heterogeneous. Identifying systematic individual differences in neuroanatomy could inform diagnosis and perso...

Research on Infant Health Diagnosis and Intelligence Development Based on Machine Learning and Health Information Statistics.

Intelligent health diagnosis for young children aims at maintaining and promoting the healthy development of young children, aiming to make young chil...

Predicting first session working alliances using deep learning algorithms: A proof-of-concept study for personalized psychotherapy.

OBJECTIVE: The aim of this proof-of-concept study is to develop a predictive model based on deep learning algorithms to predict working alliances afte...

Symmetric Convolutional and Adversarial Neural Network Enables Improved Mental Stress Classification From EEG.

Electroencephalography (EEG) is widely used for mental stress classification, but effective feature extraction and transfer across subjects remain cha...