AIMC Topic: Infant, Premature
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Feed-forward neural networks using cerebral MR spectroscopy and DTI might predict neurodevelopmental outcome in preterm neonates.
European radiology
Jul 18, 2020
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...
Humans
Infant, Premature, Diseases
Male
Infant
Predictive Value of Tests
Image Interpretation, Computer-Assisted
Infant, Premature
Developmental Disabilities
Magnetic Resonance Spectroscopy
Diffusion Tensor Imaging
Prognosis
Female
Infant, Newborn
Sensitivity and Specificity
Neural Networks, Computer
Prospective Studies
Brain
Integration of an interpretable machine learning algorithm to identify early life risk factors of childhood obesity among preterm infants: a prospective birth cohort.
BMC medicine
Jul 10, 2020
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...
Machine Learning to Support Hemodynamic Intervention in the Neonatal Intensive Care Unit.
Clinics in perinatology
May 20, 2020
Hemodynamic support in neonatal intensive care is directed at maintaining cardiovascular wellbeing. At present, monitoring of vital signs plays an essential role in augmenting care in a reactive manner. By applying machine learning techniques, a mode...
Predicting motor outcome in preterm infants from very early brain diffusion MRI using a deep learning convolutional neural network (CNN) model.
NeuroImage
Apr 9, 2020
BACKGROUND AND AIMS: Preterm birth imposes a high risk for developing neuromotor delay. Earlier prediction of adverse outcome in preterm infants is crucial for referral to earlier intervention. This study aimed to predict abnormal motor outcome at 2 ...
A convolutional neural network outperforming state-of-the-art sleep staging algorithms for both preterm and term infants.
Journal of neural engineering
Jan 14, 2020
OBJECTIVE: To classify sleep states using electroencephalogram (EEG) that reliably works over a wide range of preterm ages, as well as term age.
Preterm Infants' Pose Estimation With Spatio-Temporal Features.
IEEE transactions on bio-medical engineering
Dec 23, 2019
OBJECTIVE: Preterm infants' limb monitoring in neonatal intensive care units (NICUs) is of primary importance for assessing infants' health status and motor/cognitive development. Herein, we propose a new approach to preterm infants' limb pose estima...
Identifying fetal yawns based on temporal dynamics of mouth openings: A preterm neonate model using support vector machines (SVMs).
PloS one
Dec 19, 2019
Fetal yawning is of interest because of its clinical, developmental and theoretical implications. However, the methodological challenges of identifying yawns from ultrasonographic scans have not been systematically addressed. We report two studies th...
Cardio-respiratory signal extraction from video camera data for continuous non-contact vital sign monitoring using deep learning.
Physiological measurement
Dec 2, 2019
UNLABELLED: Non-contact vital sign monitoring enables the estimation of vital signs, such as heart rate, respiratory rate and oxygen saturation (SpO), by measuring subtle color changes on the skin surface using a video camera. For patients in a hospi...
Endocan serum concentration in uninfected newborn infants.
Journal of infection in developing countries
Sep 30, 2019
INTRODUCTION: Endocan is a specific endothelial mediator involved in the inflammatory response. Its role in the diagnosis of sepsis has been studied in adult patients and late onset neonatal sepsis. The clinical signs of early onset sepsis (EOS) are ...
Automated diagnosis and quantitative analysis of plus disease in retinopathy of prematurity based on deep convolutional neural networks.
Acta ophthalmologica
Sep 27, 2019
BACKGROUND: The purpose of this study was to develop an automated diagnosis and quantitative analysis system for plus disease. The system provides a diagnostic decision but also performs quantitative analysis of the typical pathological features of t...
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