Psychiatry

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

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Using fMRI and machine learning to predict symptom improvement following cognitive behavioural therapy for psychosis.

Cognitive behavioural therapy for psychosis (CBTp) involves helping patients to understand and refra...

Primal world beliefs.

Beck's insight-that beliefs about one's self, future, and environment shape behavior-transformed dep...

Fusing Location Data for Depression Prediction.

Recent studies have demonstrated that geographic location features collected using smartphones can b...

Potential identification of vitamin B6 responsiveness in autism spectrum disorder utilizing phenotype variables and machine learning methods.

We investigated whether machine learning methods could potentially identify a subgroup of persons wi...

Translational machine learning for psychiatric neuroimaging.

Despite its initial promise, neuroimaging has not been widely translated into clinical psychiatry to...

Fusing Near-Infrared Spectroscopy with Wearable Hemodynamic Measurements Improves Classification of Mental Stress.

Human-computer interaction (HCI) technology, and the automatic classification of a person's mental s...

Low-Rank Representation for Multi-center Autism Spectrum Disorder Identification.

Effective utilization of multi-center data for autism spectrum disorder (ASD) diagnosis recently has...

Identifying a neuroanatomical signature of schizophrenia, reproducible across sites and stages, using machine learning with structured sparsity.

OBJECTIVE: Structural MRI (sMRI) increasingly offers insight into abnormalities inherent to schizoph...

An accessible and efficient autism screening method for behavioural data and predictive analyses.

Autism spectrum disorder is associated with significant healthcare costs, and early diagnosis can su...

Learning Generalizable Recurrent Neural Networks from Small Task-fMRI Datasets.

Deep learning has become the new state-of-the-art for many problems in image analysis. However, larg...

Social Robots for Depression in Older Adults: A Systematic Review.

PURPOSE: In recent years, there has been an increase in the number of studies using social robots to...

Annual Research Review: Developmental computational psychiatry.

Most psychiatric disorders emerge during childhood and adolescence. This is also a period that coinc...

The impact of robotic intervention on joint attention in children with autism spectrum disorders.

BACKGROUND: A growing body of anecdotal evidence indicates that the use of robots may provide unique...

Parkinson's Disease Diagnosis via Joint Learning From Multiple Modalities and Relations.

Parkinson's disease (PD) is a neurodegenerative progressive disease that mainly affects the motor sy...

Mental labour.

Mental effort is an elementary notion in our folk psychology and a familiar fixture in everyday intr...

A kernel machine method for detecting higher order interactions in multimodal datasets: Application to schizophrenia.

BACKGROUND: Technological advances are enabling us to collect multimodal datasets at an increasing d...

Should Artificial Intelligence Augment Medical Decision Making? The Case for an Autonomy Algorithm.

A significant proportion of elderly and psychiatric patients do not have the capacity to make health...

Is It Ethical to Use Prognostic Estimates from Machine Learning to Treat Psychosis?

Machine learning is a method for predicting clinically relevant variables, such as opportunities for...

The Elephant in the Room: Outbreak of Carfentanil Deaths in Minnesota and the Importance of Multiagency Collaboration.

Over a three-month period in early 2017, the Hennepin County Medical Examiner's Office investigated ...

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