Psychiatry

Fully Connected Cascade Artificial Neural Network Architecture for Attention Deficit Hyperactivity Disorder Classification From Functional Magnetic Resonance Imaging Data.

Automated recognition and classification of brain diseases are of tremendous value to society. Attention deficit hyperactivity disorder (ADHD) is a diverse spectrum disorder whose diagnosis is based on behavior and hence will benefit from classification utilizing objective neuroimaging measures. Toward this end, an international competition was conducted for classifying ADHD using functional magne...

RNA splicing. The human splicing code reveals new insights into the genetic determinants of disease.

To facilitate precision medicine and whole-genome annotation, we developed a machine-learning technique that scores how strongly genetic variants affect RNA splicing, whose alteration contributes to many diseases. Analysis of more than 650,000 intronic and exonic variants revealed widespread patterns of mutation-driven aberrant splicing. Intronic disease mutations that are more than 30 nucleotides...

Validation of electronic health record phenotyping of bipolar disorder cases and controls.

OBJECTIVE: The study was designed to validate use of electronic health records (EHRs) for diagnosing bipolar disorder and classifying control subjects...

Exploring the dynamics of design fluency in children with and without ADHD using artificial neural networks.

The neuropsychology of attention deficit/hyperactivity disorder (ADHD) has been extensively studied, with a general focus on global performance measur...

Properties and Performance of Imperfect Dual Neural Network-Based kWTA Networks.

The dual neural network (DNN)-based k -winner-take-all ( k WTA) model is an effective approach for finding the k largest inputs from n inputs. Its maj...

Re: Lateral temperature spread of monopolar, bipolar and ultrasonic instruments for robot-assisted laparoscopic surgery.

A machine learning approach using auditory odd-ball responses to investigate the effect of Clozapine therapy.

OBJECTIVE: To develop a machine learning (ML) methodology based on features extracted from odd-ball auditory evoked potentials to identify neurophysio...

Predictors of schizophrenia spectrum disorders in early-onset first episodes of psychosis: a support vector machine model.

Identifying early-onset schizophrenia spectrum disorders (SSD) at a very early stage remains challenging. To assess the diagnostic predictive value of...

Diagnostic classification of specific phobia subtypes using structural MRI data: a machine-learning approach.

While neuroimaging research has advanced our knowledge about fear circuitry dysfunctions in anxiety disorders, findings based on diagnostic groups do ...

Integrating socially assistive robotics into mental healthcare interventions: applications and recommendations for expanded use.

As a field, mental healthcare is faced with major challenges as it attempts to close the huge gap between those who need services and those who receiv...

Feature Selection and Classification of Electroencephalographic Signals: An Artificial Neural Network and Genetic Algorithm Based Approach.

Feature selection is an important step in many pattern recognition systems aiming to overcome the so-called curse of dimensionality. In this study, an...

Interpretable Symptom Vectors for Depression in a Large Language Model

Patients with depression present with diverse symptom profiles, yet clinical practice routinely reduces this variation to a single severity score. Lar...

Machine learning analysis of Autism phenotype data supports a four-dimensional continuum with three overlapping subtypes

Autism Spectrum Disorder (ASD) is a heterogeneous neurodevelopmental condition defined by differences in social communication and restricted, repetiti...

SMOTE-VAR: An Uncertainty-Aware Oversampling Method for Predicting Depression Remission in University Students

University students experience disproportionately high rates of common mental health conditions, such as depression, which can impair learning, social...

TAMI: Temporally Aligned, Missingness-Aware, and Interpretable Multimodal Fusion for Mental Health Assessment in Older Adults with Mild Cognitive Impairment

Depression and anxiety in older adults with Mild Cognitive Impairment (MCI) are frequently underdiagnosed due to limited access to care. Multimodal an...

Learning Human Health and Diseases from 24-hour Wrist Movement

Much of human health and function unfolds beyond the clinic, through the movements of everyday life. Wrist-worn accelerometers capture these movements...

Auditable CT Phenotyping Through Report-derived Radiological Observations

Medical image foundation models can predict clinical phenotypes from computed tomography (CT), but strong performance leaves open whether they read di...

WISE-Screen: A Smartphone-Based Analytical Framework for Automated ASD Screening and Phenotyping via High-Fidelity Eye-tracking

The rising prevalence of autism spectrum disorder (ASD) strains clinical infrastructure. Gold-standard tools like ADOS-2 face high costs, specialized ...

SAGE: Stability-Aware Graph-Based Ensemble Feature Selection for Explainable Postpartum Depression Risk Prediction

Postpartum depression (PPD) poses a major burden on maternal and child health, especially in low- and middle-income countries where prevalence exceeds...

Large-Scale Psychiatric Concept Extraction from Electronic Health Records: A Comparative Study of Encoder-Based Language Models

Background: Free-text notes in electronic health records (EHRs) contain fine-grained psychiatric information that is essential for psychiatric researc...