Psychiatry

Predicting individual responses to the electroconvulsive therapy with hippocampal subfield volumes in major depression disorder.

Electroconvulsive therapy (ECT) is one of the most effective treatments for major depression disorder (MDD). ECT can induce neurogenesis and synaptogenesis in hippocampus, which contains distinct subfields, e.g., the cornu ammonis (CA) subfields, a granule cell layer (GCL), a molecular layer (ML), and the subiculum. It is unclear which subfields are affected by ECT and whether we predict the futur...

Multi-Site Diagnostic Classification of Schizophrenia Using Discriminant Deep Learning with Functional Connectivity MRI.

BACKGROUND: A lack of a sufficiently large sample at single sites causes poor generalizability in automatic diagnosis classification of heterogeneous psychiatric disorders such as schizophrenia based on brain imaging scans. Advanced deep learning methods may be capable of learning subtle hidden patterns from high dimensional imaging data, overcome potential site-related variation, and achieve repr...

Determining Anxiety in Obsessive Compulsive Disorder through Behavioural Clustering and Variations in Repetition Intensity.

BACKGROUND AND OBJECTIVES: Over the last decade, the application of computer vision techniques to the analysis of behavioural patterns has seen a cons...

Reflecting on the Germanwings Disaster: A Systematic Review of Depression and Suicide in Commercial Airline Pilots.

BACKGROUND: The 2015 Germanwings Flight 9525 disaster, in which 150 people were killed after the co-pilot may have intentionally crashed the plane in ...

Thalamocortical dysrhythmia detected by machine learning.

Thalamocortical dysrhythmia (TCD) is a model proposed to explain divergent neurological disorders. It is characterized by a common oscillatory pattern...

Investigating brain structural patterns in first episode psychosis and schizophrenia using MRI and a machine learning approach.

In this study, we employed the Maximum Uncertainty Linear Discriminant Analysis (MLDA) to investigate whether the structural brain patterns in first e...

Brain-specific functional relationship networks inform autism spectrum disorder gene prediction.

Autism spectrum disorder (ASD) is a neuropsychiatric disorder with strong evidence of genetic contribution, and increased research efforts have result...

Visual mental imagery: A view from artificial intelligence.

This article investigates whether, and how, an artificial intelligence (AI) system can be said to use visual, imagery-based representations in a way t...

High efficiency classification of children with autism spectrum disorder.

Autism spectrum disorder (ASD) is a wide-ranging collection of developmental diseases with varying symptoms and degrees of disability. Currently, ASD ...

Motor and psychosocial impact of robot-assisted gait training in a real-world rehabilitation setting: A pilot study.

In the last decade robotic devices have been applied in rehabilitation to overcome walking disability in neurologic diseases with promising results. R...

Machine learning in autistic spectrum disorder behavioral research: A review and ways forward.

Autistic Spectrum Disorder (ASD) is a mental disorder that retards acquisition of linguistic, communication, cognitive, and social skills and abilitie...

A YinYang bipolar fuzzy cognitive TOPSIS method to bipolar disorder diagnosis.

BACKGROUND AND OBJECTIVE: Bipolar disorder is often mis-diagnosed as unipolar depression in the clinical diagnosis. The main reason is that, different...

Identifying neuropsychiatric disorders using unsupervised clustering methods: Data and code.

This article provides data for five different neuropsychiatric disorders-Attention Deficit Hyperactivity Disorder, Alzheimer's Disease, Autism Spectru...

GWAS-based machine learning approach to predict duloxetine response in major depressive disorder.

Major depressive disorder (MDD) is one of the most prevalent psychiatric disorders and is commonly treated with antidepressant drugs. However, large v...

Predicting suicidal ideation in primary care: An approach to identify easily assessable key variables.

OBJECTIVE: To obtain predictors of suicidal ideation, which can also be used for an indirect assessment of suicidal ideation (SI). To create a classif...

Early prediction of cognitive deficits in very preterm infants using functional connectome data in an artificial neural network framework.

Investigation of the brain's functional connectome can improve our understanding of how an individual brain's organizational changes influence cogniti...

Functional Categorization of Disease Genes Based on Spectral Graph Theory and Integrated Biological Knowledge.

Interaction of multiple genetic variants is a major challenge in the development of effective treatment strategies for complex disorders. Identifying ...

Machine Learning Approaches for Clinical Psychology and Psychiatry.

Machine learning approaches for clinical psychology and psychiatry explicitly focus on learning statistical functions from multidimensional data sets ...

In Schizophrenia, Depression, Anxiety, and Physiosomatic Symptoms Are Strongly Related to Psychotic Symptoms and Excitation, Impairments in Episodic Memory, and Increased Production of Neurotoxic Tryptophan Catabolites: a Multivariate and Machine Learning Study.

The depression, anxiety and physiosomatic symptoms (DAPS) of schizophrenia are associated with negative symptoms and changes in tryptophan catabolite ...

A Biologically Inspired Approach to Frequency Domain Feature Extraction for EEG Classification.

Classification of electroencephalogram (EEG) signal is important in mental decoding for brain-computer interfaces (BCI). We introduced a feature extra...