OBJECTIVES: We aimed to evaluate the ability of feed-forward neural networks (fNNs) to predict the neurodevelopmental outcome (NDO) of very preterm neonates (VPIs) at 12 months corrected age by using biomarkers of cerebral MR proton spectroscopy (H-M...
Several studies have shown that the human gaze, but not the robot gaze, has significant effects on infant social cognition and facilitate social engagement. The present study investigates early understanding of the referential nature of gaze by compa...
American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons
Jul 15, 2020
Clinical decision-making in kidney transplant (KT) during the coronavirus disease 2019 (COVID-19) pandemic is understandably a conundrum: both candidates and recipients may face increased acquisition risks and case fatality rates (CFRs). Given our po...
BACKGROUND: The early life risk factors of childhood obesity among preterm infants are unclear and little is known about the influence of the feeding practices. We aimed to identify early life risk factors for childhood overweight/obesity among prete...
OBJECTIVE: There are no validated methods for predicting the timing of seizures. Using machine learning, we sought to forecast 24-hour risk of self-reported seizure from e-diaries.
Intracranial pressure (ICP) is an important parameter to monitor in several neuropathologies. However, because current clinically accepted methods are invasive, its monitoring is limited to patients in critical conditions. On the other hand, there ar...
Structural neural network architecture patterns in the human brain could be related to individual differences in phenotype, behavior, genetic determinants, and clinical outcomes from neuropsychiatric disorders. Recent studies have indicated that a pe...
We aimed to develop machine learning models to accurately predict bronchiolitis severity, and to compare their predictive performance with a conventional scoring (reference) model. In a 17-center prospective study of infants (aged < 1 year) hospitali...
OBJECTIVE: Automatic sleep stage scoring is of great importance for investigating sleep architecture during infancy. In this work, we introduce a novel multichannel approach based on deep learning networks and hidden Markov models (HMM) to improve th...
American journal of medical genetics. Part A
Jun 11, 2020
Angelman syndrome (AS) is caused by several genetic mechanisms that impair the expression of maternally-inherited UBE3A through deletions, paternal uniparental disomy (UPD), UBE3A pathogenic variants, or imprinting defects. Current methods of differe...