Neurology

Autism

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

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Integrative taxonomy using traits and genomic data for Species Delimitation with Deep learning

Recognizing species boundaries in complex speciation scenarios, including those involving gene flow ...

BrainDINO: A Brain MRI Foundation Model for Generalizable Clinical Representation Learning

Brain MRI underpins a wide range of neuroscientific and clinical applications, yet most learning-bas...

Scalable machine learning improves resistance prediction and identifies novel determinants in Mycobacterium tuberculosis

Multidrug-resistant and extensively drug-resistant Mycobacterium tuberculosis (MTB) represents a gro...

A Multi-modal LLM-Knowledge Fusion Framework for Predicting Single-cell Genetic Perturbation Effects

Understanding cellular responses to genetic perturbations is fundamental for drug discovery, yet exp...

Learning dynamics of unsupervised deep learning reveal epoch-specific genetic architectures of brain morphology

Representation learning is an emerging paradigm for deriving phenotypes from complex measurements (e...

Predictive Cellular Signatures from Live Human Motor Neurons Distinguish TDP-43 ALS and Enable ALS Subtype Stratification

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by the progr...

SNPic: SNP Topic Modeling for Interpretable Clustering of Complex phenotypes

Genome-wide association studies (GWAS) have cataloged thousands of disease-associated variants, yet ...

Foundation models for discovering robust biomarkers of neurological disorders from dynamic functional connectivity

Several brain foundation models (FM) have recently been proposed to predict brain disorders by model...

Predictive Modeling of Natural Medicinal Compounds for Alzheimer Disease Using Cheminformatics

The most common cause of dementia is Alzheimer disease, a progressive neurodegenerative disorder aff...

Enabling the prediction of phage receptor specificity from genome data

Predicting which receptor a phage binds to from genome sequence alone has remained an intractable ch...

CLIMB: Controllable Longitudinal Brain Image Generation using Mamba-based Latent Diffusion Model and Gaussian-aligned Autoencoder

Latent diffusion models have emerged as powerful generative models in medical imaging, enabling the ...

Strain- and age-dependent divergence in mouse appetitive spatial learning and decision strategies

Animals rely on associative spatial memory to navigate toward previously learned, reward-associated ...

Evolutionary-scale protein language models uncover beneficial variants in a Sorghum bicolor diversity panel

Quantitative genetic approaches such as genome-wide association studies and genomic prediction are w...

Unlocking Multi-Site Clinical Data: A Federated Approach to Privacy-First Child Autism Behavior Analysis

Automated recognition of autistic behaviors in children is essential for early intervention and obje...

Environment-Aware Channel Prediction for Vehicular Communications: A Multimodal Visual Feature Fusion Framework

The deep integration of communication with intelligence and sensing, as a defining vision of 6G, ren...

Developmental brain age gap in prematurity and postnatally emerging delay in congenital heart disease

Brain development follows a precisely regulated biological timetable, with defined periods of vulner...

MAMGL: A memory-augmented meta-graph learning framework for adolescent major depression disorder diagnosis

Adolescent major depressive disorder (AMDD) is a prevalent and heterogeneous psychiatric condition t...

D-GATNet: Interpretable Temporal Graph Attention Learning for ADHD Identification Using Dynamic Functional Connectivity

Attention Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder whose neu...

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