AIMC Topic: Child

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Multi-parameter machine learning approach to the neuroanatomical basis of developmental dyslexia.

Human brain mapping
Despite decades of research, the anatomical abnormalities associated with developmental dyslexia are still not fully described. Studies have focused on between-group comparisons in which different neuroanatomical measures were generally explored in i...

Individual prediction of long-term outcome in adolescents at ultra-high risk for psychosis: Applying machine learning techniques to brain imaging data.

Human brain mapping
An important focus of studies of individuals at ultra-high risk (UHR) for psychosis has been to identify biomarkers to predict which individuals will transition to psychosis. However, the majority of individuals will prove to be resilient and go on t...

Predicting proprotein convertase subtilisin kexin type-9 loss of function mutations using plasma PCSK9 concentration.

Journal of clinical lipidology
BACKGROUND: Low plasma proprotein convertase subtilisin kexin type-9 (PCSK9) concentration has been associated with loss of function (LOF) PCSK9 mutations in several studies. However, the current standard for detection of these LOF mutations is throu...

A Realistic Seizure Prediction Study Based on Multiclass SVM.

International journal of neural systems
A patient-specific algorithm, for epileptic seizure prediction, based on multiclass support-vector machines (SVM) and using multi-channel high-dimensional feature sets, is presented. The feature sets, combined with multiclass classification and post-...

Predicting symptom severity in autism spectrum disorder based on cortical thickness measures in agglomerative data.

NeuroImage
Machine learning approaches have been widely used for the identification of neuropathology from neuroimaging data. However, these approaches require large samples and suffer from the challenges associated with multi-site, multi-protocol data. We prop...

Predicting ventriculoperitoneal shunt infection in children with hydrocephalus using artificial neural network.

Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery
OBJECTIVES: The relationships between shunt infection and predictive factors have not been previously investigated using Artificial Neural Network (ANN) model. The aim of this study was to develop an ANN model to predict shunt infection in a group of...

Multiclass Classification for the Differential Diagnosis on the ADHD Subtypes Using Recursive Feature Elimination and Hierarchical Extreme Learning Machine: Structural MRI Study.

PloS one
The classification of neuroimaging data for the diagnosis of certain brain diseases is one of the main research goals of the neuroscience and clinical communities. In this study, we performed multiclass classification using a hierarchical extreme lea...

Acceptability of Robot Assistant in Management of Type 1 Diabetes in Children.

Diabetes technology & therapeutics
BACKGROUND: To find out whether children with type 1 diabetes accept a humanoid robot as an assistant in their diabetes management. In particular, the study aims to determine how the patients feel the robot may contribute to their care and how they r...