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ABSTRACT: Background
Hypoxic-ischemic encephalopathy (HIE) appears in neurological conditions where some brain areas are likely to be injured, such as deep grey matter, basal ganglia area, and white matter subcortical periventricular áreas. Moreover, modeling these brain areas in a newborn is challenging due to significant variability in the intensities associated with HIE conditions. This paper aims to evaluate functional measurements and 3D machine learning models of a given HIE case by correlating the affected brain areas with the pathophysiology and clinical neurodevelopmental.Case presentation
A comprehensive analysis of a term infant with perinatal asphyxia using longitudinal 3D brain information from Machine Learning Models is presented. The clinical analysis revealed the peri
SUBMITTER: Velasquez-Minoli JP
PROVIDER: S-EPMC11003057 | biostudies-literature | 2024 Apr
REPOSITORIES: biostudies-literature