Autism

Brain age predicted using graph convolutional neural network explains neurodevelopmental trajectory in preterm neonates.

OBJECTIVES: Dramatic brain morphological changes occur throughout the third trimester of gestation. ...

Artificial intelligence-enabled 8-lead ECG detection of atrial septal defect among adults: a novel diagnostic tool.

BACKGROUND: Patients with atrial septal defect (ASD) exhibit distinctive electrocardiogram (ECG) pat...

Domain-adaptive neural networks improve supervised machine learning based on simulated population genetic data.

Investigators have recently introduced powerful methods for population genetic inference that rely o...

A hybrid machine learning feature selection model-HMLFSM to enhance gene classification applied to multiple colon cancers dataset.

Colon cancer is a significant global health problem, and early detection is critical for improving s...

Editorial: Understanding the impact of AI and technology on the assessment, monitoring, and treatment of neurodevelopmental disorders.

Digenic Analysis Finds Highly Interactive Genetic Variants Underlying Polygenic Traits.

We briefly review our recently published approach to mining digenic genotype patterns, which consist...

An intronic genetic variant of ZHX2 predicts response to pegylated interferon α therapy in HBeAg-positive chronic hepatitis B patients.

ZHX2 plays a crucial role in host immunity and modulates hepatitis B virus (HBV) replication. Howeve...

Disparities in Diagnosis, Access to Specialist Care and Treatment for Inborn Errors of Immunity.

Inborn errors of immunity represent a rapidly expanding group of genetic disorders of the immune sys...

EGeRepDR: An enhanced genetic-based representation learning for drug repurposing using multiple biomedical sources.

MOTIVATION: Drug repurposing (DR) is an imminent approach for identifying novel therapeutic indicati...

Predicting Autism from Head Movement Patterns during Naturalistic Social Interactions.

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized in part by difficulti...

c-Diadem: a constrained dual-input deep learning model to identify novel biomarkers in Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is an incurable, debilitating neurodegenerative disorder. Curre...

Learning Sequential Information in Task-based fMRI for Synthetic Data Augmentation.

Insufficiency of training data is a persistent issue in medical image analysis, especially for task-...

Applications for Deep Learning in Epilepsy Genetic Research.

Epilepsy is a group of brain disorders characterised by an enduring predisposition to generate unpro...

Machine Learning Differentiation of Autism Spectrum Sub-Classifications.

PURPOSE: Disorders on the autism spectrum have characteristics that can manifest as difficulties wit...

TranStutter: A Convolution-Free Transformer-Based Deep Learning Method to Classify Stuttered Speech Using 2D Mel-Spectrogram Visualization and Attention-Based Feature Representation.

Stuttering, a prevalent neurodevelopmental disorder, profoundly affects fluent speech, causing invol...

Clinical Feature Ranking Based on Ensemble Machine Learning Reveals Top Survival Factors for Glioblastoma Multiforme.

Glioblastoma multiforme (GM) is a malignant tumor of the central nervous system considered to be hig...

Using ChatGPT to predict the future of personalized medicine.

Personalized medicine is a novel frontier in health care that is based on each person's unique genet...

Harnessing deep learning for population genetic inference.

In population genetics, the emergence of large-scale genomic data for various species and population...

A longitudinal observational study on the epidemiology of painful procedures and sucrose administration in hospitalized preterm neonates.

Although sucrose is widely administered to hospitalized infants for single painful procedures, total...

Modeling islet enhancers using deep learning identifies candidate causal variants at loci associated with T2D and glycemic traits.

Genetic association studies have identified hundreds of independent signals associated with type 2 d...

Predicting transcriptional outcomes of novel multigene perturbations with GEARS.

Understanding cellular responses to genetic perturbation is central to numerous biomedical applicati...