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...
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...
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...
International journal of neural systems
Sep 23, 2016
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-...
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...
Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery
Sep 14, 2016
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...
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...
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...
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