AIMC Topic: Infant, Premature

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A machine learning investigation of volumetric and functional MRI abnormalities in adults born preterm.

Human brain mapping Jun 22, 2019
Imaging studies have characterized functional and structural brain abnormalities in adults after premature birth, but these investigations have mostly used univariate methods that do not account for hypothesized interdependencies between brain region...
Humans Machine Learning Brain Longitudinal Studies Magnetic Resonance Imaging Brain Mapping Image Interpretation, Computer-Assisted Infant, Premature Female Infant, Newborn Adult Male
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Enhanced early prediction of clinically relevant neonatal hyperbilirubinemia with machine learning.

Pediatric research Mar 31, 2019
BACKGROUND: Machine learning models may enhance the early detection of clinically relevant hyperbilirubinemia based on patient information available in every hospital.
Hyperbilirubinemia, Neonatal Phototherapy Bilirubin Infant, Premature Gestational Age Humans Female Machine Learning Regression Analysis Infant, Newborn ROC Curve Retrospective Studies Area Under Curve Sensitivity and Specificity Longitudinal Studies Internet Male
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Pilot Testing a Robot for Reducing Pain in Hospitalized Preterm Infants.

OTJR : occupation, participation and health Feb 15, 2019
Optimizing neurodevelopment is a key goal of neonatal occupational therapy. In preterm infants, repeated procedural pain is associated with adverse effects on neurodevelopment long term. Calmer is a robot designed to reduce infant pain. The objective...
Male Pilot Projects Treatment Outcome Robotics Occupational Therapy Humans Female Infant, Newborn Infant Care Pain Infant, Premature Intensive Care Units, Neonatal Child, Hospitalized
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Deep Learning for Image Quality Assessment of Fundus Images in Retinopathy of Prematurity.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Accurate image-based medical diagnosis relies upon adequate image quality and clarity. This has important implications for clinical diagnosis, and for emerging methods such as telemedicine and computer-based image analysis. In this study, we trained ...
Telemedicine Infant, Premature Retinopathy of Prematurity Neural Networks, Computer Algorithms Humans Infant, Newborn Deep Learning Reproducibility of Results ROC Curve Area Under Curve Fundus Oculi Retina
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Predictive connectome subnetwork extraction with anatomical and connectivity priors.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Aug 25, 2018
We present a new method to identify anatomical subnetworks of the human connectome that are optimally predictive of targeted clinical variables, developmental outcomes or disease states. Given a training set of structural or functional brain networks...
Anatomic Landmarks Autistic Disorder Infant, Premature Connectome Machine Learning Infant, Newborn Magnetic Resonance Imaging Humans Predictive Value of Tests
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Quiet sleep detection in preterm infants using deep convolutional neural networks.

Journal of neural engineering Aug 22, 2018
OBJECTIVE: Neonates spend most of their time asleep. Sleep of preterm infants evolves rapidly throughout maturation and plays an important role in brain development. Since visual labelling of the sleep stages is a time consuming task, automated analy...
Wakefulness Sleep Automation Infant, Premature Female Infant, Newborn Male Electroencephalography Sleep Stages Humans Neural Networks, Computer Algorithms Brain
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17-hydroxiprogesterone values in healthy preterm infants.

Colombia medica (Cali, Colombia) Dec 30, 2017
INTRODUCTION: In preterm newborn, problems with the interpretation of 17-OHP may occur.
Birth Weight Infant, Premature Neonatal Screening Gestational Age 17-alpha-Hydroxyprogesterone Adrenal Hyperplasia, Congenital Humans Female Infant, Newborn Male Cohort Studies Enzyme-Linked Immunosorbent Assay Longitudinal Studies Follow-Up Studies
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Machine learning shows association between genetic variability in and cerebral connectivity in preterm infants.

Proceedings of the National Academy of Sciences of the United States of America Dec 11, 2017
Preterm infants show abnormal structural and functional brain development, and have a high risk of long-term neurocognitive problems. The molecular and cellular mechanisms involved are poorly understood, but novel methods now make it possible to addr...
Humans Female Infant, Newborn Male Machine Learning Brain PPAR gamma Polymorphism, Single Nucleotide Diffusion Tensor Imaging RNA-Binding Proteins Integrin alpha6 Infant, Premature Connectome
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BrainNetCNN: Convolutional neural networks for brain networks; towards predicting neurodevelopment.

NeuroImage Sep 28, 2016
We propose BrainNetCNN, a convolutional neural network (CNN) framework to predict clinical neurodevelopmental outcomes from brain networks. In contrast to the spatially local convolutions done in traditional image-based CNNs, our BrainNetCNN is compo...
Diffusion Tensor Imaging Infant, Premature, Diseases Neurodevelopmental Disorders Male Neural Networks, Computer Brain Mapping Brain Humans Infant, Premature Female Infant, Newborn Neural Pathways
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Prediction of brain maturity in infants using machine-learning algorithms.

NeuroImage May 11, 2016
Recent resting-state functional MRI investigations have demonstrated that much of the large-scale functional network architecture supporting motor, sensory and cognitive functions in older pediatric and adult populations is present in term- and prema...
Reproducibility of Results Pattern Recognition, Automated Humans Sensitivity and Specificity Brain Infant, Premature Algorithms Image Enhancement Magnetic Resonance Imaging Regression Analysis Prognosis Brain Mapping Female Gestational Age Image Interpretation, Computer-Assisted Infant, Newborn Male Support Vector Machine
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