AIMC Topic: Infant, Premature, Diseases

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Development of a machine learning model for prediction of intraventricular hemorrhage in premature neonates.

Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery Dec 16, 2024
PURPOSE: Intraventricular hemorrhage (IVH) is a common and severe complication in premature neonates, leading to long-term neurological impairments. Early prediction and identification of risk factors for IVH in premature neonates are crucial for imp...
Infant, Premature, Diseases Cerebral Intraventricular Hemorrhage Algorithms Retrospective Studies Female Infant, Newborn Cerebral Hemorrhage Infant, Premature Gestational Age Risk Factors Male Humans Machine Learning
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Early prediction of mortality and morbidities in VLBW preterm neonates using machine learning.

Pediatric research Oct 8, 2024
BACKGROUND: Predicting mortality and specific morbidities before they occur may allow for interventions that may improve health trajectories.
Algorithms Retrospective Studies Female Infant, Newborn Humans Machine Learning Infant Mortality Infant, Premature Infant, Premature, Diseases Enterocolitis, Necrotizing Infant, Very Low Birth Weight Male Bronchopulmonary Dysplasia ROC Curve Morbidity
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Predicting early mortality and severe intraventricular hemorrhage in very-low birth weight preterm infants: a nationwide, multicenter study using machine learning.

Scientific reports May 12, 2024
Our aim was to develop a machine learning-based predictor for early mortality and severe intraventricular hemorrhage (IVH) in very-low birth weight (VLBW) preterm infants in Taiwan. We collected retrospective data from VLBW infants, dividing them int...
Humans Machine Learning Male Infant Taiwan Cerebral Hemorrhage Birth Weight Prognosis Retrospective Studies Female Infant, Newborn Cerebral Intraventricular Hemorrhage Infant Mortality Infant, Very Low Birth Weight Infant, Premature Gestational Age Infant, Premature, Diseases
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Machine learning-based analysis for prediction of surgical necrotizing enterocolitis in very low birth weight infants using perinatal factors: a nationwide cohort study.

European journal of pediatrics Mar 30, 2024
Early prediction of surgical necrotizing enterocolitis (sNEC) in preterm infants is important. However, owing to the complexity of the disease, identifying infants with NEC at a high risk for surgical intervention is difficult. We developed a machine...
Enterocolitis, Necrotizing Infant, Very Low Birth Weight Registries Infant, Premature Gestational Age Infant, Premature, Diseases Retrospective Studies Republic of Korea Female Infant, Newborn Humans Risk Factors Male Risk Assessment Cohort Studies Machine Learning
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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...
Neurodevelopmental Disorders Infant, Newborn Adult Male Middle Aged Machine Learning Infant, Premature Child Databases, Factual Models, Neurological Developmental Disabilities Humans Brain Infant, Premature, Diseases Female
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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...
Infant, Newborn Sensitivity and Specificity Male Infant Predictive Value of Tests Image Interpretation, Computer-Assisted Infant, Premature Developmental Disabilities Prospective Studies Brain Prognosis Female Humans Neural Networks, Computer Magnetic Resonance Spectroscopy Diffusion Tensor Imaging Infant, Premature, Diseases
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Estimating risk of severe neonatal morbidity in preterm births under 32 weeks of gestation.

The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians Jul 18, 2018
A large recent study analyzed the relationship between multiple factors and neonatal outcome and in preterm births. Study variables included the reason for admission, indication for delivery, optimal steroid use, gestational age, and other potential...
Diagnostic Techniques, Obstetrical and Gynecological Infant, Small for Gestational Age Risk Factors Adult Probability Pregnancy Humans Male Infant Female Gestational Age Infant Mortality Machine Learning Risk Assessment Severity of Illness Index Infant, Newborn Stillbirth Prospective Studies Predictive Value of Tests Premature Birth Infant, Premature, Diseases Prognosis Morbidity
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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...
Neural Pathways Diffusion Tensor Imaging Infant, Premature, Diseases Neurodevelopmental Disorders Infant, Newborn Male Brain Mapping Infant, Premature Humans Neural Networks, Computer Brain Female
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A Potential Solution to Plus Disease Variability.

Ophthalmology. Retina Oct 1, 2020
Retinopathy of Prematurity Infant, Premature, Diseases Humans Infant, Newborn Deep Learning
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