Autism

Multibranch Attention and Fusion Network for Voice-Based Autism Detection Using Heterogeneous Audio Embeddings.

Voice-based analysis is attracting growing interest as a noninvasive means of identifying early markers of autism spectrum disorder (ASD). While pretrained audio models such as YAMNet and VGGish provide complementary views of children's speech, most existing studies rely on a single representation and do not explore how these embeddings may be combined in a structured manner. This work introduces ...

Early-Life Exposure to Organophosphorus Pesticide Mixtures and Impaired Neonatal Neurodevelopment: A Cohort Study Integrating Comprehensive Multi-Omics and Machine Learning.

Early-life exposure to low-dose organophosphorus pesticide (OPP) mixtures and their impact on neonatal neurodevelopment remain insufficiently characterized. In this study, plasma samples from 281 newborns were analyzed for 21 OPPs, and neurodevelopment was assessed using the Neonatal Behavioral Neurological Assessment (NBNA). Mixture models consistently identified fenamiphos and fenitrothion as ma...

Organoid intelligence: a promising paradigm for autism spectrum disorder research.

Autism spectrum disorder (ASD) is a multifactorial neurodevelopmental condition marked by heterogeneity in its clinical presentations, which complicat...

Artificial Intelligence in Neuromuscular Diseases: Opportunities for a Data-Scarce Field.

Neuromuscular diseases (NMDs) encompass over 800 distinct entities affecting approximately one in 1000 individuals worldwide, with progressive muscle ...

Vaginal drug delivery for precision therapy in polyendocrine metabolic ovarian syndrome: emerging technologies, translational challenges and future perspectives.

INTRODUCTION: Polyendocrine Metabolic Ovarian Syndrome (PMOS) is an endocrine disorder characterized by metabolic dysfunction, hormonal imbalance, inf...

Risk Assessment in MASLD and MetALD: Current Approaches and Future Directions.

Metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction and alcohol-related liver disease (MetALD) exist on a conti...

From clinical and typical separation to autism spectrum disorder and global developmental delay differentiation: Interpretable eye-tracking-based machine learning.

In clinical practice, objectively distinguishing children with autism spectrum disorder (ASD) from those with typical development (TD) and other neuro...

Development of Perinatal Social Determinants of Health Composite Risk Score in Infants Born Preterm.

OBJECTIVE: To develop and validate a perinatal social determinant of health (SDoH) risk score for predicting neurodevelopmental outcomes in infants bo...

Virtual single-cell perturbation and genetic causal inference reveal CSF1R-dependent immunometabolic communication in iron metabolism-associated osteoarthritis.

Iron dysregulation has emerged as a contributor to osteoarthritis (OA), yet the cell-communication mechanisms connecting iron-related genetic signals ...

Cutaneous lymphomas - an update.

Primary cutaneous lymphomas (CL) and lymphoproliferative disorders (LPD) are heterogeneous T- and B-cell neoplasms defined by integrated clinical, his...

Leveraging synthetic and genetic data to improve epidemic forecasting.

Forecasting infectious disease outbreaks is hard. Forecasting emerging infectious diseases with limited historical data is even harder. In this paper,...

Translating evolutionary history and protein-focused machine learning supports increased prevalence of hereditary haemorrhagic telangiectasia, one of the most common inherited disorders.

BACKGROUND: Recent genetic data suggest hereditary haemorrhagic telangiectasia (HHT) is 2-12 times more common than the clinically-ascertained prevale...

MSPPGT: A Multi-Scale Pyramid Pooling-Based Graph Transformer Framework for Neuropsychiatric Disorder Diagnosis.

Graph Neural Networks (GNNs) model functional connectivity patterns between brain regions via neighborhood information aggregation. However, most GNN ...

Group Favoritism in Children With Autism Spectrum Disorders.

People tend to evaluate more positively the members of their group. This study examined this behavior in autistic children to better understand the st...

AMR-VSF: an adaptive memory correction framework for robust 3D CT aorta segmentation.

PURPOSE: Accurate 3D aortic segmentation in CT images is vital for cardiovascular disease diagnosis, surgical planning, and intraoperative navigation....

Epigenetic markers expand genetic risk estimation in acute myeloid leukemia.

Gene mutations and chromosome abnormalities are important components of prognostication in acute myeloid leukemia (AML). Here we assessed whether DNA ...

Metasurface color routers inverse-designed with a deep-learning accelerated genetic algorithm for high efficiency imaging.

Full-wave electromagnetic simulations provide accurate field distributions for nanophotonic structures, but their high computational cost limits their...

Pathogenic Genetic Variants, Comorbid Autism and Adaptive Developmental Quotient as Independent Predictors of Intellectual Disability in Children With Global Developmental Delay: An Interpretable Machine Learning Model With Calibrated Risk Estimation.

BACKGROUND: Global developmental delay (GDD) frequently precedes intellectual disability (ID), but no validated multivariable prognostic tool exists t...

A Risk Prediction Model for Normal-Tension Glaucoma Progression Integrating Genetic Markers and Corneal Biomechanics.

OBJECTIVE: Normal-tension glaucoma (NTG) is characterized by progressive optic nerve damage despite intraocular pressure remaining consistently within...

An integrated systems biology and machine learning framework for identifying potential biomarkers and pathways in autism spectrum disorder.

BACKGROUND: Autism spectrum disorders (ASD) are a group of neurodevelopmental disorders whose underlying molecular mechanisms and biological processes...