AIMC Topic: Hypoxia-Ischemia, Brain

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Validation of a machine learning algorithm for identifying infants at risk of hypoxic ischaemic encephalopathy in a large unseen data set.

Archives of disease in childhood. Fetal and neonatal edition Apr 17, 2025
OBJECTIVE: To validate a hypoxic ischaemic encephalopathy (HIE) prediction algorithm to identify infants at risk of HIE immediately after birth using readily available clinical data.
Apgar Score Humans Female Male Infant, Newborn Risk Assessment Hypoxia-Ischemia, Brain Machine Learning Algorithms
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Updates in Neonatal Seizures.

Clinics in perinatology Apr 1, 2025
Neonatal seizures are a common medical emergency, necessitating prompt treatment. The most common etiologies include hypoxic-ischemic encephalopathy, ischemic stroke, and intracranial hemorrhage, with numerous other uncommon etiologies. Accurate diag...
Humans Seizures Artificial Intelligence Prognosis Hypoxia-Ischemia, Brain Infant, Newborn Anticonvulsants Phenobarbital Electroencephalography
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Automated Neuroprognostication Via Machine Learning in Neonates with Hypoxic-Ischemic Encephalopathy.

Annals of neurology Dec 10, 2024
OBJECTIVES: Neonatal hypoxic-ischemic encephalopathy is a serious neurologic condition associated with death or neurodevelopmental impairments. Magnetic resonance imaging (MRI) is routinely used for neuroprognostication, but there is substantial subj...
Humans Machine Learning Brain Hypothermia, Induced Male Prognosis Hypoxia-Ischemia, Brain Infant Female Magnetic Resonance Imaging Infant, Newborn
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Machine learning for forecasting initial seizure onset in neonatal hypoxic-ischemic encephalopathy.

Epilepsia Nov 4, 2024
OBJECTIVE: This study was undertaken to develop a machine learning (ML) model to forecast initial seizure onset in neonatal hypoxic-ischemic encephalopathy (HIE) utilizing clinical and quantitative electroencephalogram (QEEG) features.
Male Electroencephalography Seizures Hypoxia-Ischemia, Brain Forecasting Female Infant, Newborn Humans Machine Learning
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Machine learning models of cerebral oxygenation (rcSO) for brain injury detection in neonates with hypoxic-ischaemic encephalopathy.

The Journal of physiology Oct 19, 2024
The present study was designed to test the potential utility of regional cerebral oxygen saturation (rcSO) in detecting term infants with brain injury. The study also examined whether quantitative rcSO features are associated with grade of hypoxic is...
Infant, Newborn Male Magnetic Resonance Imaging Prospective Studies Brain Female Hypoxia-Ischemia, Brain Brain Injuries Oxygen Oxygen Saturation Humans Machine Learning
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Free access via computational cloud to deep learning-based EEG assessment in neonatal hypoxic-ischemic encephalopathy: revolutionary opportunities to overcome health disparities.

Pediatric research Aug 6, 2024
In this issue of Pediatric Research, Kota et al. evaluate a novel monitoring visual trend using deep-learning - Brain State of the Newborn (BSN)- based EEG as a bedside marker for severity of the encephalopathy in 46 neonates with hypoxic-ischemic en...
Hypoxia-Ischemia, Brain Humans Brain Infant, Newborn Deep Learning Electroencephalography Healthcare Disparities
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Rule-based deep learning method for prognosis of neonatal hypoxic-ischemic encephalopathy by using susceptibility weighted image analysis.

Magma (New York, N.Y.) Jan 22, 2024
OBJECTIVE: Susceptibility weighted imaging (SWI) of neonatal hypoxic-ischemic brain injury can provide assistance in the prognosis of neonatal hypoxic-ischemic encephalopathy (HIE). We propose a convolutional neural network model to classify SWI imag...
Humans Brain Hypoxia-Ischemia, Brain Prognosis Child, Preschool Infant, Newborn Magnetic Resonance Imaging Deep Learning Datasets as Topic
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Deep Learning to Optimize Magnetic Resonance Imaging Prediction of Motor Outcomes After Hypoxic-Ischemic Encephalopathy.

Pediatric neurology Sep 7, 2023
BACKGROUND: Magnetic resonance imaging (MRI) is the gold standard for outcome prediction after hypoxic-ischemic encephalopathy (HIE). Published scoring systems contain duplicative or conflicting elements.
Deep Learning Magnetic Resonance Imaging Gestational Age Humans Hypoxia-Ischemia, Brain Infant Diffusion Magnetic Resonance Imaging
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Graphic Intelligent Diagnosis of Hypoxic-Ischemic Encephalopathy Using MRI-Based Deep Learning Model.

Neonatology May 25, 2023
INTRODUCTION: Heterogeneous MRI manifestations restrict the efficiency and consistency of neuroradiologists in diagnosing hypoxic-ischemic encephalopathy (HIE) due to complex injury patterns. This study aimed to develop and validate an intelligent HI...
Hypoxia-Ischemia, Brain Case-Control Studies Deep Learning Magnetic Resonance Imaging Humans Retrospective Studies Infant, Newborn
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Prediction of obstetrical and fetal complications using automated electronic health record data.

American journal of obstetrics and gynecology Oct 22, 2020
An increasing number of delivering women experience major morbidity and mortality. Limited work has been done on automated predictive models that could be used for prevention. Using only routinely collected obstetrical data, this study aimed to devel...
Hypoxia-Ischemia, Brain Stillbirth Clinical Decision Rules Pre-Eclampsia Obstetric Labor Complications Premature Birth Maternal Age Parity Pregnancy in Obesity Adult Postpartum Hemorrhage Reproducibility of Results Humans Routinely Collected Health Data Electronic Health Records Time Factors Machine Learning Uterine Rupture Blood Pressure Retrospective Studies Pregnancy Female
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