Psychiatry

Telehealth in Mental Health Nursing Education: Health Care Simulation With Remote Presence Technology.

The feasibility of integrating remote presence technology within a simulation scenario for psychiatric-mental health nursing (PMHN) students to develop telehealth competencies was evaluated. A wireless, audiovisual robot from Double® Robotics, maneuverable by smartphone or tablet computer, was used to simulate the facilitation of students' patient assessment and treatment decisions from a distant ...

Brain Morphometry Methods for Feature Extraction in Random Subspace Ensemble Neural Network Classification of First-Episode Schizophrenia.

Machine learning (ML) is a growing field that provides tools for automatic pattern recognition. The neuroimaging community currently tries to take advantage of ML in order to develop an auxiliary diagnostic tool for schizophrenia diagnostics. In this letter, we present a classification framework based on features extracted from magnetic resonance imaging (MRI) data using two automatic whole-brain ...

Considering patient safety in autonomous e-mental health systems - detecting risk situations and referring patients back to human care.

BACKGROUND: Digital health interventions can fill gaps in mental healthcare provision. However, autonomous e-mental health (AEMH) systems also present...

Combining heterogeneous data sources for neuroimaging based diagnosis: re-weighting and selecting what is important.

Combining neuroimaging and clinical information for diagnosis, as for example behavioral tasks and genetics characteristics, is potentially beneficial...

Predicting hospital-acquired pneumonia among schizophrenic patients: a machine learning approach.

BACKGROUND: Medications are frequently used for treating schizophrenia, however, anti-psychotic drug use is known to lead to cases of pneumonia. The p...

Artificial intelligence based discovery of the association between depression and chronic fatigue syndrome.

BACKGROUND: Both of the modern medicine and the traditional Chinese medicine classify depressive disorder (DD) and chronic fatigue syndrome (CFS) to o...

Predicting one-year outcome in first episode psychosis using machine learning.

BACKGROUND: Early illness course correlates with long-term outcome in psychosis. Accurate prediction could allow more focused intervention. Earlier in...

Job interview training targeting nonverbal communication using an android robot for individuals with autism spectrum disorder.

Job interviews are significant barriers for individuals with autism spectrum disorder because these individuals lack good nonverbal communication skil...

Modelling PTSD diagnosis using sleep, memory, and adrenergic metabolites: An exploratory machine-learning study.

OBJECTIVE: Features of posttraumatic stress disorder (PTSD) typically include sleep disturbances, impaired declarative memory, and hyperarousal. This ...

Robust water-fat separation for multi-echo gradient-recalled echo sequence using convolutional neural network.

PURPOSE: To accurately separate water and fat signals for bipolar multi-echo gradient-recalled echo sequence using a convolutional neural network (CNN...

Machine Learning, Natural Language Processing, and the Electronic Health Record: Innovations in Mental Health Services Research.

An unprecedented amount of clinical information is now available via electronic health records (EHRs). These massive data sets have stimulated opportu...

EEG-based mild depression recognition using convolutional neural network.

Electroencephalography (EEG)-based studies focus on depression recognition using data mining methods, while those on mild depression are yet in infanc...

Identification of suicidal behavior among psychiatrically hospitalized adolescents using natural language processing and machine learning of electronic health records.

OBJECTIVE: The rapid proliferation of machine learning research using electronic health records to classify healthcare outcomes offers an opportunity ...

Low-rank network signatures in the triple network separate schizophrenia and major depressive disorder.

Brain imaging studies have revealed that functional and structural brain connectivity in the so-called triple network (i.e., default mode network (DMN...

The Early Psychosis Screener for Internet (EPSI)-SR: Predicting 12 month psychotic conversion using machine learning.

INTRODUCTION: A faster and more accurate self-report screener for early psychosis is needed to promote early identification and intervention.

A randomized controlled trial of suicide prevention training for primary care providers: a study protocol.

BACKGROUND: Suicide is a national public health crisis and a critical patient safety issue. It is the 10th leading cause of death overall and the seco...

Machine learning in mental health: a scoping review of methods and applications.

BACKGROUND: This paper aims to synthesise the literature on machine learning (ML) and big data applications for mental health, highlighting current re...

Detection of abnormal behaviour for dementia sufferers using Convolutional Neural Networks.

In recent years, there is a rapid increase in the population of elderly people. However, elderly people may suffer from the consequences of cognitive ...

Electroconvulsive Therapy Induces Cortical Morphological Alterations in Major Depressive Disorder Revealed with Surface-Based Morphometry Analysis.

Although electroconvulsive therapy (ECT) is one of the most effective treatments for major depressive disorder (MDD), the mechanism underlying the the...

Predicting inadequate postoperative pain management in depressed patients: A machine learning approach.

Widely-prescribed prodrug opioids (e.g., hydrocodone) require conversion by liver enzyme CYP-2D6 to exert their analgesic effects. The most commonly p...