Psychiatry

[Artificial intelligence in psychiatry-an overview].

Artificial intelligence and the underlying methods of machine learning and neuronal networks (NN) ha...

Machine learning approach for early detection of autism by combining questionnaire and home video screening.

BACKGROUND: Existing screening tools for early detection of autism are expensive, cumbersome, time- ...

Depression Severity Classification from Speech Emotion.

Major Depressive Disorder (MDD) is a common psychiatric illness. Automatically classifying depressio...

Anatomical Biomarkers for Adolescent Major Depressive Disorder from Diffusion Weighted Imaging using SVM Classifier.

Adolescent Major Depressive Disorder (MDD) is a common and serious mental illness that could lead to...

Classifying Treated vs. Untreated MDD Adolescents from Anatomical Connectivity using Nonlinear SVM.

Identification of the treatment-related responders for adolescent Major Depressive Disorder (MDD) is...

Applying Machine-Learning Techniques to Build Self-reported Depression Prediction Models.

Measuring Use of Evidence Based Psychotherapy for Posttraumatic Stress Disorder in a Large National Healthcare System.

To derive a method of identifying use of evidence-based psychotherapy (EBP) for post-traumatic stres...

Using Unsupervised Machine Learning to Identify Subgroups Among Home Health Patients With Heart Failure Using Telehealth.

This study explored the use of unsupervised machine learning to identify subgroups of patients with ...

A Sibling-Mediated Intervention for Children with Autism Spectrum Disorder: Using the Natural Language Paradigm (NLP).

We taught three typically developing siblings to occasion speech by implementing the Natural Languag...

Predicting Autism Spectrum Disorder Using Domain-Adaptive Cross-Site Evaluation.

The advances in neuroimaging methods reveal that resting-state functional fMRI (rs-fMRI) connectivit...

Differences Between Schizophrenic and Normal Subjects Using Network Properties from fMRI.

Schizophrenia has been proposed to result from impairment of functional connectivity. We aimed to us...

Impressions of Humanness for Android Robot may Represent an Endophenotype for Autism Spectrum Disorders.

Identification of meaningful endophenotypes may be critical to unraveling the etiology and pathophys...

AI opens new frontier for suicide prevention.

Factors Associated with HIV Viral Suppression Among Transgender Women in Lima, Peru.

PURPOSE: Globally, transgender women (TGW) experience a high burden of adverse health outcomes, incl...

Automatic Detection of Depression by Using a Neural Network.

Depression is the most common psychiatric disorder worldwide, which affects more than 300 million pe...

Predicting Depression Among Community Residing Older Adults: A Use of Machine Learning Approch.

The study demonstrated an application of machine learning techniques in building a depression predic...

A New Machine Learning Framework for Understanding the Link Between Cannabis Use and First-Episode Psychosis.

Lately, several studies started to investigate the existence of links between cannabis use and psych...

Refining Prediction in Treatment-Resistant Depression: Results of Machine Learning Analyses in the TRD III Sample.

OBJECTIVE: The study objective was to generate a prediction model for treatment-resistant depression...

A New Local Bipolar Autoassociative Memory Based on External Inputs of Discrete Recurrent Neural Networks With Time Delay.

In this paper, local bipolar auto-associative memories are presented based on discrete recurrent neu...

Talking to Machines About Personal Mental Health Problems.

Distributed Intrinsic Functional Connectivity Patterns Predict Diagnostic Status in Large Autism Cohort.

Diagnosis of autism spectrum disorder (ASD) currently relies on behavioral observations because brai...