Neurology

Autism

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

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Digenic Analysis Finds Highly Interactive Genetic Variants Underlying Polygenic Traits.

We briefly review our recently published approach to mining digenic genotype patterns, which consist...

Disparities in Diagnosis, Access to Specialist Care and Treatment for Inborn Errors of Immunity.

Inborn errors of immunity represent a rapidly expanding group of genetic disorders of the immune sys...

An intronic genetic variant of ZHX2 predicts response to pegylated interferon α therapy in HBeAg-positive chronic hepatitis B patients.

ZHX2 plays a crucial role in host immunity and modulates hepatitis B virus (HBV) replication. Howeve...

EGeRepDR: An enhanced genetic-based representation learning for drug repurposing using multiple biomedical sources.

MOTIVATION: Drug repurposing (DR) is an imminent approach for identifying novel therapeutic indicati...

Predicting Autism from Head Movement Patterns during Naturalistic Social Interactions.

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized in part by difficulti...

c-Diadem: a constrained dual-input deep learning model to identify novel biomarkers in Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is an incurable, debilitating neurodegenerative disorder. Curre...

AI interprets the Central Dogma and Genetic Code.

Generative artificial intelligence (AI) is a burgeoning field with widespread applications, includin...

Learning Sequential Information in Task-based fMRI for Synthetic Data Augmentation.

Insufficiency of training data is a persistent issue in medical image analysis, especially for task-...

An automatic progressive chromosome segmentation approach using deep learning with traditional image processing.

The fully automatic chromosome analysis system plays an important role in the detection of genetic d...

Applications for Deep Learning in Epilepsy Genetic Research.

Epilepsy is a group of brain disorders characterised by an enduring predisposition to generate unpro...

Machine Learning Differentiation of Autism Spectrum Sub-Classifications.

PURPOSE: Disorders on the autism spectrum have characteristics that can manifest as difficulties wit...

Analysis of Prospective Genetic Indicators for Prenatal Exposure to Arsenic in Newborn Cord Blood of Using Machine Learning.

Using a machine learning methods, we aim to find biological effect biomarkers of prenatal arsenic ex...

Clinical Feature Ranking Based on Ensemble Machine Learning Reveals Top Survival Factors for Glioblastoma Multiforme.

Glioblastoma multiforme (GM) is a malignant tumor of the central nervous system considered to be hig...

Using ChatGPT to predict the future of personalized medicine.

Personalized medicine is a novel frontier in health care that is based on each person's unique genet...

Novel tools for early diagnosis and precision treatment based on artificial intelligence.

Lung cancer has the highest mortality rate among all cancers in the world. Hence, early diagnosis an...

Harnessing deep learning for population genetic inference.

In population genetics, the emergence of large-scale genomic data for various species and population...

A longitudinal observational study on the epidemiology of painful procedures and sucrose administration in hospitalized preterm neonates.

Although sucrose is widely administered to hospitalized infants for single painful procedures, total...

Modeling islet enhancers using deep learning identifies candidate causal variants at loci associated with T2D and glycemic traits.

Genetic association studies have identified hundreds of independent signals associated with type 2 d...

Predicting transcriptional outcomes of novel multigene perturbations with GEARS.

Understanding cellular responses to genetic perturbation is central to numerous biomedical applicati...

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