Neurology

Autism

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

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Estimating the refractive index of oxygenated and deoxygenated hemoglobin using genetic algorithm - support vector regression model.

BACKGROUND AND OBJECTIVES: The refractive index of hemoglobin plays important role in hematology due...

A computational framework for the detection of subcortical brain dysmaturation in neonatal MRI using 3D Convolutional Neural Networks.

Deep neural networks are increasingly being used in both supervised learning for classification task...

Deep-Learning Convolutional Neural Networks Accurately Classify Genetic Mutations in Gliomas.

BACKGROUND AND PURPOSE: The World Health Organization has recently placed new emphasis on the integr...

Using machine learning to identify patterns of lifetime health problems in decedents with autism spectrum disorder.

Very little is known about the health problems experienced by individuals with autism spectrum disor...

Risk Assessment for Parents Who Suspect Their Child Has Autism Spectrum Disorder: Machine Learning Approach.

BACKGROUND: Parents are likely to seek Web-based communities to verify their suspicions of autism sp...

A machine learning based framework to identify and classify long terminal repeat retrotransposons.

Transposable elements (TEs) are repetitive nucleotide sequences that make up a large portion of euka...

A hierarchical clustering method for dimension reduction in joint analysis of multiple phenotypes.

Genome-wide association studies (GWAS) have become a very effective research tool to identify geneti...

GGDonto ontology as a knowledge-base for genetic diseases and disorders of glycan metabolism and their causative genes.

BACKGROUND: Inherited mutations in glyco-related genes can affect the biosynthesis and degradation o...

Design and validation of an ontology-driven animal-free testing strategy for developmental neurotoxicity testing.

Developmental neurotoxicity entails one of the most complex areas in toxicology. Animal studies prov...

Brain-specific functional relationship networks inform autism spectrum disorder gene prediction.

Autism spectrum disorder (ASD) is a neuropsychiatric disorder with strong evidence of genetic contri...

DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network.

BACKGROUND: Medical practitioners use survival models to explore and understand the relationships be...

High efficiency classification of children with autism spectrum disorder.

Autism spectrum disorder (ASD) is a wide-ranging collection of developmental diseases with varying s...

Machine learning in autistic spectrum disorder behavioral research: A review and ways forward.

Autistic Spectrum Disorder (ASD) is a mental disorder that retards acquisition of linguistic, commun...

Neuroanatomical morphometric characterization of sex differences in youth using statistical learning.

Exploring neuroanatomical sex differences using a multivariate statistical learning approach can yie...

Identifying neuropsychiatric disorders using unsupervised clustering methods: Data and code.

This article provides data for five different neuropsychiatric disorders-Attention Deficit Hyperacti...

GWAS-based machine learning approach to predict duloxetine response in major depressive disorder.

Major depressive disorder (MDD) is one of the most prevalent psychiatric disorders and is commonly t...

Early prediction of cognitive deficits in very preterm infants using functional connectome data in an artificial neural network framework.

Investigation of the brain's functional connectome can improve our understanding of how an individua...

Functional Categorization of Disease Genes Based on Spectral Graph Theory and Integrated Biological Knowledge.

Interaction of multiple genetic variants is a major challenge in the development of effective treatm...

Risk-Predicting Model for Incident of Essential Hypertension Based on Environmental and Genetic Factors with Support Vector Machine.

Essential hypertension (EH) has become a major chronic disease around the world. To build a risk-pre...

Prediction of opioid dose in cancer pain patients using genetic profiling: not yet an option with support vector machine learning.

OBJECTIVE: Use of opioids for pain management has increased over the past decade; however, inadequat...

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