AIMC Topic: Infant, Premature

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Deep learning-based parameter estimation in fetal diffusion-weighted MRI.

NeuroImage Aug 26, 2021
Diffusion-weighted magnetic resonance imaging (DW-MRI) of fetal brain is challenged by frequent fetal motion and signal to noise ratio that is much lower than non-fetal imaging. As a result, accurate and robust parameter estimation in fetal DW-MRI re...
Neural Networks, Computer Infant, Newborn Reproducibility of Results Deep Learning Fetus Gestational Age Anisotropy Image Processing, Computer-Assisted Humans Diffusion Magnetic Resonance Imaging Motion Infant, Premature Signal-To-Noise Ratio
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Assistive Framework for Automatic Detection of All the Zones in Retinopathy of Prematurity Using Deep Learning.

Journal of digital imaging Jul 8, 2021
Retinopathy of prematurity (ROP) is a potentially blinding disorder seen in low birth weight preterm infants. In India, the burden of ROP is high, with nearly 200,000 premature infants at risk. Early detection through screening and treatment can prev...
Humans Infant, Newborn Infant, Low Birth Weight Deep Learning Retinopathy of Prematurity Retina Infant, Premature
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Automated Explainable Multidimensional Deep Learning Platform of Retinal Images for Retinopathy of Prematurity Screening.

JAMA network open May 3, 2021
IMPORTANCE: A retinopathy of prematurity (ROP) diagnosis currently relies on indirect ophthalmoscopy assessed by experienced ophthalmologists. A deep learning algorithm based on retinal images may facilitate early detection and timely treatment of RO...
Humans Neonatal Screening Ophthalmoscopy Retinopathy of Prematurity Male Deep Learning Area Under Curve Female Infant, Premature Infant, Newborn Sensitivity and Specificity
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Key factors in a rigorous longitudinal image-based assessment of retinopathy of prematurity.

Scientific reports Mar 8, 2021
To describe a database of longitudinally graded telemedicine retinal images to be used as a comparator for future studies assessing grader recall bias and ability to detect typical progression (e.g. International Classification of Retinopathy of Prem...
Humans Artificial Intelligence Female Infant, Premature Ophthalmoscopy Retinopathy of Prematurity Infant, Newborn Male Image Processing, Computer-Assisted Telemedicine
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Deep Learning for EEG Seizure Detection in Preterm Infants.

International journal of neural systems Jan 30, 2021
EEG is the gold standard for seizure detection in the newborn infant, but EEG interpretation in the preterm group is particularly challenging; trained experts are scarce and the task of interpreting EEG in real-time is arduous. Preterm infants are re...
Epilepsy Seizures Infant, Premature Humans Infant, Newborn Infant Deep Learning Electroencephalography
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Automatic segmentation of ventricular volume by 3D ultrasonography in post haemorrhagic ventricular dilatation among preterm infants.

Scientific reports Jan 12, 2021
To train, evaluate, and validate the application of a deep learning framework in three-dimensional ultrasound (3D US) for the automatic segmentation of ventricular volume in preterm infants with post haemorrhagic ventricular dilatation (PHVD). We tra...
Software Design Heart Ventricles Hypertrophy Infant, Premature Dilatation, Pathologic Deep Learning Humans Ultrasonography Neural Networks, Computer Imaging, Three-Dimensional Image Processing, Computer-Assisted Organ Size Breast Infant, Newborn Sensitivity and Specificity
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Fast body part segmentation and tracking of neonatal video data using deep learning.

Medical & biological engineering & computing Oct 23, 2020
Photoplethysmography imaging (PPGI) for non-contact monitoring of preterm infants in the neonatal intensive care unit (NICU) is a promising technology, as it could reduce medical adhesive-related skin injuries and associated complications. For practi...
Video Recording Infant, Premature Human Body Infant Deep Learning Image Processing, Computer-Assisted Humans Photoplethysmography Infant, Newborn
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A multi-task, multi-stage deep transfer learning model for early prediction of neurodevelopment in very preterm infants.

Scientific reports Sep 15, 2020
Survivors following very premature birth (i.e., ≤ 32 weeks gestational age) remain at high risk for neurodevelopmental impairments. Recent advances in deep learning techniques have made it possible to aid the early diagnosis and prognosis of neurodev...
Male Middle Aged Child Models, Neurological Infant, Premature Developmental Disabilities Neurodevelopmental Disorders Infant, Premature, Diseases Brain Humans Female Machine Learning Infant, Newborn Databases, Factual Adult
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Automated detection of early-stage ROP using a deep convolutional neural network.

The British journal of ophthalmology Aug 23, 2020
BACKGROUND/AIM: To automatically detect and classify the early stages of retinopathy of prematurity (ROP) using a deep convolutional neural network (CNN).
Infant, Low Birth Weight Gestational Age Retinopathy of Prematurity Cross-Sectional Studies Male ROC Curve Humans Retrospective Studies Diagnosis, Computer-Assisted Image Processing, Computer-Assisted Female Neural Networks, Computer Birth Weight Infant, Newborn Algorithms Infant, Premature Sensitivity and Specificity
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Reliability and accuracy of EEG interpretation for estimating age in preterm infants.

Annals of clinical and translational neurology Aug 7, 2020
OBJECTIVES: To determine the accuracy of, and agreement among, EEG and aEEG readers' estimation of maturity and a novel computational measure of functional brain age (FBA) in preterm infants.
Brain Diseases Humans Reproducibility of Results Infant, Premature Machine Learning Diagnosis, Computer-Assisted Gestational Age Brain Predictive Value of Tests Neonatology Infant, Newborn Electroencephalography
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