Neurology

Autism

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

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Deep Learning for Population Genetic Inference.

Given genomic variation data from multiple individuals, computing the likelihood of complex populati...

A Genetic Algorithm and Fuzzy Logic Approach for Video Shot Boundary Detection.

This paper proposed a shot boundary detection approach using Genetic Algorithm and Fuzzy Logic. In t...

Extracting genetic alteration information for personalized cancer therapy from ClinicalTrials.gov.

OBJECTIVE: Clinical trials investigating drugs that target specific genetic alterations in tumors ar...

Extending unified-theory-of-reinforcement neural networks to steady-state operant behavior.

The unified theory of reinforcement has been used to develop models of behavior over the last 20 yea...

Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls.

Neuroimaging-based single subject prediction of brain disorders has gained increasing attention in r...

Genes with high penetrance for syndromic and non-syndromic autism typically function within the nucleus and regulate gene expression.

BACKGROUND: Intellectual disability (ID), autism, and epilepsy share frequent yet variable comorbidi...

HYDRA: Revealing heterogeneity of imaging and genetic patterns through a multiple max-margin discriminative analysis framework.

Multivariate pattern analysis techniques have been increasingly used over the past decade to derive ...

Inference and Analysis of Population Structure Using Genetic Data and Network Theory.

Clustering individuals to subpopulations based on genetic data has become commonplace in many geneti...

Minimalistic toy robot to analyze a scenery of speaker-listener condition in autism.

Atypical neural architecture causes impairment in communication capabilities and reduces the ability...

Use of machine learning for behavioral distinction of autism and ADHD.

Although autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) continue...

Synthetic collective intelligence.

Intelligent systems have emerged in our biosphere in different contexts and achieving different leve...

Robots Learn to Recognize Individuals from Imitative Encounters with People and Avatars.

Prior to language, human infants are prolific imitators. Developmental science grounds infant imitat...

A knowledgebase of the human Alu repetitive elements.

Alu elements are the most abundant retrotransposons in the human genome with more than one million c...

Multivariate Analyses Applied to Healthy Neurodevelopment in Fetal, Neonatal, and Pediatric MRI.

Multivariate analysis (MVA) is a class of statistical and pattern recognition techniques that involv...

Neuro-genetic system for optimization of GMI samples sensitivity.

Magnetic sensors are largely used in several engineering areas. Among them, magnetic sensors based o...

Controlling Individuals Growth in Semantic Genetic Programming through Elitist Replacement.

In 2012, Moraglio and coauthors introduced new genetic operators for Genetic Programming, called geo...

Using Genetic Programming with Prior Formula Knowledge to Solve Symbolic Regression Problem.

A researcher can infer mathematical expressions of functions quickly by using his professional knowl...

Transcriptomes of lineage-specific Drosophila neuroblasts profiled by genetic targeting and robotic sorting.

A brain consists of numerous distinct neurons arising from a limited number of progenitors, called n...

Prediction of Synergism from Chemical-Genetic Interactions by Machine Learning.

The structure of genetic interaction networks predicts that, analogous to synthetic lethal interacti...

Shedding Light on Synergistic Chemical Genetic Connections with Machine Learning.

Machine learning can be used to predict compounds acting synergistically, and this could greatly exp...

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