Neurology

Autism

Latest AI and machine learning research in autism for healthcare professionals.

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Automatic variant prioritization in suspected genetic kidney disease using the Nephro Candidate Score (N-CS)

Despite the identification of >700 genes linked to rare and inherited kidney diseases (IKD), many in...

Fragile X Syndrome in Brazil: Development and Validation of a Clinical Checklist for Population Screening

Fragile X Syndrome (FXS) is the most common inherited cause of intellectual disability and syndromic...

Discovering latent subtypes of preterm birth and genetic risk using tensor decomposition on electronic health records

Preterm birth is a syndrome that is triggered by diverse biological pathways and presents with many ...

Oxytocin Enhances Social-Emotional Reciprocity in Autism

We evaluated whether oxytocin improves social-emotional reciprocity in children and adolescents with...

CSF Proteomics and Machine Learning Reveal Distinct Stages Across the Alzheimer’s Disease Continuum

Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by heterogeneous pathophysiol...

Quantitative EEG-Based Deep Learning for Neonatal Seizure Detection using Conv-LSTM

Neonatal seizures cause significant morbidity and mortality, both acutely and in the long term, cont...

Prediction of Adolescent Internalizing Disorder Risk: Evidence from the Norwegian Mother, Father, and Child Cohort Study

Internalizing disorders are among the most common psychiatric conditions in adolescence, often assoc...

Scaling genetic discovery for organ volumes using machine learning-assisted imputation and bias-corrected GWAS

MRI-derived organ and tissue volumes are powerful endophenotypes for studying complex disease, but t...

Rule-out test for autism using machine-learning analysis of molecular temporal dynamics in hair - a multicenter study

Early intervention can improve autism-related outcomes. However, no valid biosignature test exists y...

REECAP: Contrastive learning of retinal aging reveals genetic loci linking morphology to eye disease

Deep learning foundation models excel at disease prediction from medical images, yet their potential...

A Novel Method to Disentangle Tightly Linked Risk and Resilience Genes for Brain Disorders: Application to Alzheimer’s Disease

Genetic risk factors for neuropsychiatric disorders are well documented. However, some individuals w...

Deep-learning-derived glaucoma-related endophenotypes enable novel genome-wide genetic and functional discovery

The genetic architecture of primary open-angle glaucoma (POAG), a leading cause of irreversible blin...

Incorporating Dietary Information to Enhance Polygenic Prediction Models with Applications to Body Mass Index and Type 2 Diabetes

Polygenic predictors can enhance screening for biomedical conditions, such as metabolism-related tra...

Shared genetic architecture of brain age gap across 30 cohorts worldwide

Deviations from normative brain ageing trajectories are linked to a wide range of adverse health out...

ML-Guided GWAS Reveals Genetic Architectures for MASLD for Overweight and Lean Individuals in the All of Us Cohort

Metabolic dysfunction-associated steatotic liver disease (MASLD) arises from excessive hepatic fat a...

Exploring Machine Learning Models to Uncover Pathways in ALS Pathogenesis Using Immunohistochemical Features

Amyotrophic Lateral Sclerosis (ALS) is a degenerative disease of motor neurons that leads to muscle ...

Heterogeneous epigenetic variation converges on splicing dysregulation in opioid addiction

Disease heterogeneity presents a major challenge for genetic and epigenetic dissection of complex tr...

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