Psychiatry

A Mobile Health Application to Predict Postpartum Depression Based on Machine Learning.

BACKGROUND: Postpartum depression (PPD) is a disorder that often goes undiagnosed. The development o...

Searching for a minimal set of behaviors for autism detection through feature selection-based machine learning.

Although the prevalence of autism spectrum disorder (ASD) has risen sharply in the last few years re...

Comparison of machine classification algorithms for fibromyalgia: neuroimages versus self-report.

UNLABELLED: Recent studies have posited that machine learning (ML) techniques accurately classify in...

Machine learning approaches for integrating clinical and imaging features in late-life depression classification and response prediction.

OBJECTIVE: Currently, depression diagnosis relies primarily on behavioral symptoms and signs, and tr...

Using trend templates in a neonatal seizure algorithm improves detection of short seizures in a foetal ovine model.

Seizures below one minute in duration are difficult to assess correctly using seizure detection algo...

Spontaneous motion on two-dimensional continuous attractors.

Attractor models are simplified models used to describe the dynamics of firing rate profiles of a po...

Discrimination of schizophrenia auditory hallucinators by machine learning of resting-state functional MRI.

Auditory hallucinations (AH) are a symptom that is most often associated with schizophrenia, but pat...

Fully Connected Cascade Artificial Neural Network Architecture for Attention Deficit Hyperactivity Disorder Classification From Functional Magnetic Resonance Imaging Data.

Automated recognition and classification of brain diseases are of tremendous value to society. Atten...

Validation of electronic health record phenotyping of bipolar disorder cases and controls.

OBJECTIVE: The study was designed to validate use of electronic health records (EHRs) for diagnosing...

Exploring the dynamics of design fluency in children with and without ADHD using artificial neural networks.

The neuropsychology of attention deficit/hyperactivity disorder (ADHD) has been extensively studied,...

Properties and Performance of Imperfect Dual Neural Network-Based kWTA Networks.

The dual neural network (DNN)-based k -winner-take-all ( k WTA) model is an effective approach for f...

Re: Lateral temperature spread of monopolar, bipolar and ultrasonic instruments for robot-assisted laparoscopic surgery.

A machine learning approach using auditory odd-ball responses to investigate the effect of Clozapine therapy.

OBJECTIVE: To develop a machine learning (ML) methodology based on features extracted from odd-ball ...

Predictors of schizophrenia spectrum disorders in early-onset first episodes of psychosis: a support vector machine model.

Identifying early-onset schizophrenia spectrum disorders (SSD) at a very early stage remains challen...

Diagnostic classification of specific phobia subtypes using structural MRI data: a machine-learning approach.

While neuroimaging research has advanced our knowledge about fear circuitry dysfunctions in anxiety ...

Integrating socially assistive robotics into mental healthcare interventions: applications and recommendations for expanded use.

As a field, mental healthcare is faced with major challenges as it attempts to close the huge gap be...

Feature Selection and Classification of Electroencephalographic Signals: An Artificial Neural Network and Genetic Algorithm Based Approach.

Feature selection is an important step in many pattern recognition systems aiming to overcome the so...

A comparison of machine learning methods for classification using simulation with multiple real data examples from mental health studies.

BACKGROUND: Recent literature on the comparison of machine learning methods has raised questions abo...

Biomechanical analysis on neurotypical and autism spectrum disorder people during human-cobot interaction.

Biomechanical analysis is essential for assessing subjects interacting with robotic setups and platf...

Decoding chronic stress: From behavioral-molecular dynamics in mice to clinical implications of cortisol and IL-17 in depression severity.

BACKGROUNDS: The etiology of depression involves chronic stress, a recognized determinant of onset a...

Machine learning-based predictive modeling of depressive symptoms in Chinese adolescents.

BACKGROUND: The aim is to develop prediction models by lifestyles indicators as well as socioeconomi...