Psychiatry

Latest AI and machine learning research in psychiatry for healthcare professionals.

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PRA-Net: Part-and-Relation Attention Network for depression recognition from facial expression.

Artificial intelligence methods are widely applied to depression recognition and provide an objectiv...

Towards a versatile mental workload modeling using neurometric indices.

Researchers have been working to magnify mental workload (MWL) modeling for a long time. An importan...

Effect of robot-assisted gait training on quality of life and depression in neurological impairment: A systematic review and meta-analysis.

OBJECTIVE: Robot-assisted gait training (RAGT) is often used as a rehabilitation tool for neurologic...

Computing personalized brain functional networks from fMRI using self-supervised deep learning.

A novel self-supervised deep learning (DL) method is developed to compute personalized brain functio...

Predicting dropout from psychological treatment using different machine learning algorithms, resampling methods, and sample sizes.

The occurrence of dropout from psychological interventions is associated with poor treatment outcom...

Qualitative and Artificial Intelligence-based Sentiment Analyses of Anti-LGBTI+ Hate Speech on Twitter in Turkey.

The aim of this study was to evaluate hate speech in Turkish LGBTI+-related tweets during a one-mont...

Wearable Artificial Intelligence for Anxiety and Depression: Scoping Review.

BACKGROUND: Anxiety and depression are the most common mental disorders worldwide. Owing to the lack...

Classification of Depression and Its Severity Based on Multiple Audio Features Using a Graphical Convolutional Neural Network.

Audio features are physical features that reflect single or complex coordinated movements in the voc...

Application of Natural Language Processing (NLP) in Detecting and Preventing Suicide Ideation: A Systematic Review.

(1) Introduction: Around a million people are reported to die by suicide every year, and due to the ...

Prediction of Tinnitus Treatment Outcomes Based on EEG Sensors and TFI Score Using Deep Learning.

Tinnitus is a hearing disorder that is characterized by the perception of sounds in the absence of a...

Emotional Variance Analysis: A new sentiment analysis feature set for Artificial Intelligence and Machine Learning applications.

Sentiment Analysis (SA) is a category of data mining techniques that extract latent representations ...

Degree of Accuracy With Which Deep Learning for Ultrasound Images Identifies Osteochondritis Dissecans of the Humeral Capitellum.

BACKGROUND: Medical screening using ultrasonography (US) has been performed on young baseball player...

Classification Approach for Attention Assessment via Singular Spectrum Analysis Based on Single-Channel Electroencephalograms.

Attention refers to the human psychological ability to focus on doing an activity. The attention ass...

Constrained neuro fuzzy inference methodology for explainable personalised modelling with applications on gene expression data.

Interpretable machine learning models for gene expression datasets are important for understanding t...

Deep-Learning-Based ADHD Classification Using Children's Skeleton Data Acquired through the ADHD Screening Game.

The identification of attention deficit hyperactivity disorder (ADHD) in children, which is increasi...

Behaviour recommendations with a deep learning model and genetic algorithm for health debt characterisation.

Human behaviour is a dense longitudinal multi-featured measure that directly impacts the health of i...

Enabling Remote Responder Bio-Signal Monitoring in a Cooperative Human-Robot Architecture for Search and Rescue.

The roles of emergency responders are challenging and often physically demanding, so it is essential...

Predicting childhood and adolescent attention-deficit/hyperactivity disorder onset: a nationwide deep learning approach.

Attention-deficit/hyperactivity disorder (ADHD) is a heterogeneous disorder with a high degree of ps...

Computer-aided diagnosis of autism spectrum disorder from EEG signals using deep learning with FAWT and multiscale permutation entropy features.

Autism spectrum disorder (ASD), a neurodevelopment disorder, is characterized by significant difficu...

Depression Detection Based on Hybrid Deep Learning SSCL Framework Using Self-Attention Mechanism: An Application to Social Networking Data.

In today's world, mental health diseases have become highly prevalent, and depression is one of the ...

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