Psychiatry

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

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Machine Learning Algorithms in Suicide Prevention: Clinician Interpretations as Barriers to Implementation.

OBJECTIVE: Machine learning algorithms in electronic medical records can classify patients by suicid...

Machine Learning Based Suicide Ideation Prediction for Military Personnel.

Military personnel have greater psychological stress and are at higher suicide attempt risk compared...

A double-hit of stress and low-grade inflammation on functional brain network mediates posttraumatic stress symptoms.

Growing evidence indicates a reciprocal relationship between low-grade systemic inflammation and str...

Predicting hospital readmission in patients with mental or substance use disorders: A machine learning approach.

OBJECTIVE: Mental or substance use disorders (M/SUD) are major contributors of disease burden with h...

Neural memory plasticity for medical anomaly detection.

In the domain of machine learning, Neural Memory Networks (NMNs) have recently achieved impressive r...

Ensemble Deep Learning on Large, Mixed-Site fMRI Datasets in Autism and Other Tasks.

Deep learning models for MRI classification face two recurring problems: they are typically limited ...

Neuronal mechanisms for sequential activation of memory items: Dynamics and reliability.

In this article we present a biologically inspired model of activation of memory items in a sequence...

A social robot intervention on depression, loneliness, and quality of life for Taiwanese older adults in long-term care.

OBJECTIVES: To investigate the effect of a social robot intervention on depression, loneliness, and ...

Prediction of physical violence in schizophrenia with machine learning algorithms.

Patients with schizophrenia have been shown to have an increased risk for physical violence. While c...

Noise can speed backpropagation learning and deep bidirectional pretraining.

We show that the backpropagation algorithm is a special case of the generalized Expectation-Maximiza...

Multivariate patterns of EEG microstate parameters and their role in the discrimination of patients with schizophrenia from healthy controls.

Quasi-stable electrical fields in the EEG, called microstates carry information on the dynamics of l...

Predicting mental health problems in adolescence using machine learning techniques.

BACKGROUND: Predicting which children will go on to develop mental health symptoms as adolescents is...

Detecting Abnormal Brain Regions in Schizophrenia Using Structural MRI via Machine Learning.

Utilizing neuroimaging and machine learning (ML) to differentiate schizophrenia (SZ) patients from n...

Machine-Learning prediction of comorbid substance use disorders in ADHD youth using Swedish registry data.

BACKGROUND: Children with attention-deficit/hyperactivity disorder (ADHD) have a high risk for subst...

Recognizing states of psychological vulnerability to suicidal behavior: a Bayesian network of artificial intelligence applied to a clinical sample.

BACKGROUND: This study aimed to determine conditional dependence relationships of variables that con...

Will machine learning applied to neuroimaging in bipolar disorder help the clinician? A critical review and methodological suggestions.

OBJECTIVES: The existence of anatomofunctional brain abnormalities in bipolar disorder (BD) is now w...

Feature optimization method for machine learning-based diagnosis of schizophrenia using magnetoencephalography.

BACKGROUND: When many features and a small number of clinical data exist, previous studies have used...

Multi-modular AI Approach to Streamline Autism Diagnosis in Young Children.

Autism has become a pressing healthcare challenge. The instruments used to aid diagnosis are time an...

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