Autism

KSNet: Advancing autism prediction via KAN-based graph convolution and multi-source data fusion.

Integrating functional brain networks and Graph Convolutional Networks (GCN) architecture reveal promising diagnostic capabilities for brain disorders. Prevailing approaches remain constrained when capturing dynamic nonlinearities, characterizing intricate connectomes, and fusing heterogeneous data sources. To address these limitations, we present KSNet, a novel architectural grounded in graph con...

Hybrid groupers-moray orangutan optimization algorithm-based dense-resolution network for autism spectrum disorder detection using multimodal data.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder involving cognitive and social impairments. Precise diagnosis is vital for effective intervention. However, conventional diagnostic techniques exhibited poor generalization, and high error rates while dealing with subtle patterns in neuroimaging or behavioral datasets. To resolve these concerns, this research introduces the Groupers a...

Quantitative pathology and APOE genotype reveal dementia risk and progression in Lewy body disease.

Dementia in Lewy body diseases (LBD) is common and arises through heterogeneous and incompletely understood pathways. Evidence suggests contributions ...

Social compatibility in opposite-sex prairie vole pairs is modulated by early-life sleep experience.

Studies of human social behavior indicate stronger social affinity in matched-neurotype dyads (e.g., two individuals with autism or two without) compa...

Measuring Accuracy (Classification Probabilities, Positive, and Negative Predictive Values) of Executive Function Electroencephalogram Metrics in Attention-Deficit/Hyperactivity Disorder Diagnosis: Protocol for and Perspectives From the SINCRONIA Study.

BACKGROUND: Attention deficit/hyperactivity disorder (ADHD) is the most prevalent neurodevelopmental disorder worldwide, affecting approximately 5%-7%...

Comparison of cognitive ability and its distribution between men with autism spectrum disorder and attention-deficit/hyperactivity disorder.

OBJECTIVES: Clarification of the strengths and weaknesses of cognitive ability is essential to our understanding of the characteristics of autism spec...

Baseline symptom severity and response to multisession cathodal transcranial direct current stimulation in adolescents and young adults with autism: an exploratory analysis.

BACKGROUND: Identifying baseline clinical characteristics associated with treatment response is crucial for optimising intervention strategies in peop...

Syntaxin1A in synaptopathies: From molecular mechanisms to therapeutic implications in neurological disorders (Review).

Syntaxin1A (STX1A) is a presynaptic membrane protein that is abundantly expressed in the central nervous system. It is a key member of the soluble N-e...

Clinically Confirmed Cohort Reveals Antioxidant Genetic Polymorphisms as Potential Susceptibility Factors for Long COVID After Mild or Asymptomatic COVID-19.

Although the COVID-19 pandemic has now been down-graded, long COVID (LC) presents an ongoing risk of long-term disease for a significant percentage of...

Beyond Percutaneous Coronary Intervention - Targeted Molecular Therapies for the Next Era of Coronary Care.

Coronary artery disease (CAD) remains the leading global cause of cardiovascular morbidity and mortality, driven by dysregulated lipid metabolism, chr...

Deep learning-based precision phenotyping of spine curvature identifies novel genetic risk loci for scoliosis in the UK Biobank.

Scoliosis is the most common developmental spinal deformity, but its genetic underpinnings remain only partially understood. To identify scoliosis-rel...

Incorporating valuable prior knowledge to improve deep learning prediction of genetic perturbation responses.

Genetic perturbation response prediction plays a critical role in virtual cell research, yet the performance of current deep learning models still lea...

Technology Matters: Ambient voice technology in mental health and neurodevelopmental settings - considerations for responsible implementation and evidence gaps.

Documentation comprises a large proportion of Child and Adolescent Mental Health Service (CAMHS) clinicians/practitioners' work burden and is often co...

Multimodal AI for Alzheimer Disease Diagnosis: Systematic Review of Datasets, Models, and Modalities.

BACKGROUND: Early detection of Alzheimer disease (AD) is essential for timely intervention; yet, diagnostic performance varies widely across modalitie...

[Construction and teaching practice of an AI- and OBE-integrated smart course Genetic Engineering].

Several critical challenges exist in the graduate course Genetic Engineering at Beijing Institute of Technology, including conceptual confusion in cor...

Intraventricular hemorrhage in preterm infants: A systematic review of risk- and outcome-prediction models.

Intraventricular hemorrhage (IVH) is a major complication of prematurity and one of the top causes of mortality and neurodevelopmental impairment. We ...

Optimized Complex-Valued Spatio-Temporal Graph Convolutional Networks for attention deficit hyperactivity disorder detection in pediatric EEG signals.

Attention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental condition affecting mood, anxiety, learning, and sleep. Electroencephalogram (...

Understanding tens of thousands of pockmarks and domes using machine learning (Gulf of Lions, NW Mediterranean Sea).

A broad spectrum of seabed deformation structures, including pockmarks and domes, related to various processes, have been observed on continental marg...

OptiSyn: an interpretable, multi-omics-driven graph convolutional network framework for synergy-oriented drug combination design in disease treatment.

BACKGROUND: Bioinformatics and large-scale computational modelling have emerged as essential research fields in modern biomedical science, enabling dr...

Artificial Intelligence in Neurocritical Care : Multimodal Biosignal Analysis for Prognosis, Monitoring, and Future Pediatric Applications.

Neurocritical care relies on continuous assessment of neurological function and physiology under time pressure, yet bedside teams must interpret high-...