Psychiatry

Problematic internet use (PIU): Associations with the impulsive-compulsive spectrum. An application of machine learning in psychiatry.

Problematic internet use is common, functionally impairing, and in need of further study. Its relati...

Thought-Controlled Nanoscale Robots in a Living Host.

We report a new type of brain-machine interface enabling a human operator to control nanometer-size ...

Support vector machine model of developmental brain gene expression data for prioritization of Autism risk gene candidates.

MOTIVATION: Autism spectrum disorders (ASD) are a group of neurodevelopmental disorders with clinica...

Multiclass Classification for the Differential Diagnosis on the ADHD Subtypes Using Recursive Feature Elimination and Hierarchical Extreme Learning Machine: Structural MRI Study.

The classification of neuroimaging data for the diagnosis of certain brain diseases is one of the ma...

Automated Assessment of Patients' Self-Narratives for Posttraumatic Stress Disorder Screening Using Natural Language Processing and Text Mining.

Patients' narratives about traumatic experiences and symptoms are useful in clinical screening and d...

Accuracy of automated classification of major depressive disorder as a function of symptom severity.

BACKGROUND: Growing evidence documents the potential of machine learning for developing brain based ...

Connectivity of the anterior insula differentiates participants with first-episode schizophrenia spectrum disorders from controls: a machine-learning study.

BACKGROUND: Early diagnosis of schizophrenia could improve the outcomes and limit the negative effec...

Non-reward neural mechanisms in the orbitofrontal cortex.

Single neurons in the primate orbitofrontal cortex respond when an expected reward is not obtained, ...

Machine-learning-based diagnosis of schizophrenia using combined sensor-level and source-level EEG features.

Recently, an increasing number of researchers have endeavored to develop practical tools for diagnos...

Machine learning, statistical learning and the future of biological research in psychiatry.

Psychiatric research has entered the age of 'Big Data'. Datasets now routinely involve thousands of ...

Atypical Asymmetry for Processing Human and Robot Faces in Autism Revealed by fNIRS.

Deficits in the visual processing of faces in autism spectrum disorder (ASD) individuals may be due ...

Spectral feature extraction of EEG signals and pattern recognition during mental tasks of 2-D cursor movements for BCI using SVM and ANN.

Brain computer interface (BCI) is a new communication way between man and machine. It identifies men...

Can Artificial Intelligences Suffer from Mental Illness? A Philosophical Matter to Consider.

The potential for artificial intelligences and robotics in achieving the capacity of consciousness, ...

Diagnostic Classification of ADHD Versus Control: Support Vector Machine Classification Using Brief Neuropsychological Assessment.

Common methods for clinical diagnosis include clinical interview, behavioral questionnaires, and ne...

Dynamic cerebral reorganization in the pathophysiology of schizophrenia: a MRI-derived cortical thickness study.

BACKGROUND: A structural neuroanatomical change indicating a reduction in brain tissue is a notable ...

Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records.

Secondary use of electronic health records (EHRs) promises to advance clinical research and better i...

Generating Gene Ontology-Disease Inferences to Explore Mechanisms of Human Disease at the Comparative Toxicogenomics Database.

Strategies for discovering common molecular events among disparate diseases hold promise for improvi...

Network-based classification of ADHD patients using discriminative subnetwork selection and graph kernel PCA.

BACKGROUND: Attention Deficit Hyperactivity Disorder (ADHD) is one of the most prevalent behavioral ...

Use of machine learning to improve autism screening and diagnostic instruments: effectiveness, efficiency, and multi-instrument fusion.

BACKGROUND: Machine learning (ML) provides novel opportunities for human behavior research and clini...

Letter to the Editor: Suicide as a complex classification problem: machine learning and related techniques can advance suicide prediction - a reply to Roaldset (2016).

Using neuroimaging to help predict the onset of psychosis.

The aim of this review is to assess the potential for neuroimaging measures to facilitate prediction...