Neurology

Autism

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

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BrainCHEF: Cross-Level Hypergraph Enhanced Fusion model for brain networks.

Modeling the dynamic characteristics of functional brain networks is of great significance for uncov...

MVT-Net: A novel cervical tumour segmentation using multi-view feature transfer learning.

Cervical cancer is one of the most aggressive malignant tumours of the reproductive system, posing a...

Born to Fear the Machine? Genetic and Environmental Influences on Negative Attitudes toward AI Agents.

Despite the rapid development of artificial intelligence (AI) agents, substantial individual differe...

Cold receptor TRPM8 as a target for migraine-associated pain and affective comorbidities.

BACKGROUND: Genetic variations in the Trpm8 gene that encodes the cold receptor TRPM8 have been link...

Assessing individual genetic susceptibility to metabolic syndrome: interpretable machine learning method.

BACKGROUND: Genome-wide association studies have provided profound insights into the genetic aetiolo...

Applying multimodal AI to physiological waveforms improves genetic prediction of cardiovascular traits.

Electronic health records, biobanks, and wearable biosensors enable the collection of multiple healt...

Few shot learning for phenotype-driven diagnosis of patients with rare genetic diseases.

There are over 7000 rare diseases, some affecting 3500 or fewer patients in the United States. Due t...

A New Insight in Cellular and Molecular Signaling Regulation for Neural Differentiation Program.

Numerous neurological conditions impact the brain, spinal cord, and nerves, including neurodegenerat...

A compact encoding of the genome suitable for machine learning prediction of traits and genetic risk scores.

Genotype to phenotype prediction is a central problem in biology and medicine. Machine learning is a...

Integrating AI and genomics: predictive CNN models for schizophrenia phenotypes.

This study explores the use of deep learning to analyze genetic data and predict phenotypic traits a...

Morphological traits and machine learning for genetic lineage prediction of two reef-building corals.

Integrating multiple lines of evidence that support molecular taxonomy analysis has proven to be a r...

Metastatic hepatic carcinoma: Mechanisms, emerging therapeutics, and future perspectives.

Metastatic hepatic carcinoma (MHC) remains a lethal disease, with a 5-year survival rate of around 1...

Advanced molecular approaches to thalassemia disorder and the selection of molecular-level diagnostic testing in resource-limited settings.

Beta-thalassemia is a genetic disorder that significantly burdens healthcare systems globally. This ...

Stereotactic Body Radiation Therapy for Primary Renal Cancer and Genetic Markers of Response: A Phase 2 Trial.

Controlled outcome assessment of radiotherapy for primary renal cell carcinoma (RCC) remains limited...

Optimizing stroke detection with genetic algorithm-based feature selection in deep learning models.

Brain stroke is a leading cause of disability and mortality worldwide, necessitating the development...

From neurotoxicity to neuroprotection: Rethinking GABAR-targeting anesthetics.

The brain growth spurt (BGS) represents a pivotal window in neurodevelopment, defined by rapid neuro...

AI-driven techniques for detection and mitigation of SARS-CoV-2 spread: a review, taxonomy, and trends.

The SARS-CoV-2 RNA virus, with its rapid spread and frequent genetic changes, has posed unparalleled...

Toward a general framework for AI-enabled prediction in crop improvement.

A theoretical framework for AI and ensembled prediction for crop improvement is introduced and demon...

Air Pollution and Autism Spectrum Disorder: Unveiling Multipollutant Risks and Sociodemographic Influences in California.

BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental condition with increasing prevale...

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