Dimensionality Reduction in Neonatal Seizure Outcomes: A Factor Analysis Approach
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Keywords

neonatal seizures
risk factors
epilepsy
mortality
logistic regression
decision tree

How to Cite

[1]
U. C. L. (UCL) and U. Kingdom., “Dimensionality Reduction in Neonatal Seizure Outcomes: A Factor Analysis Approach”, J. Comput. Eng., vol. 11, no. 10, Oct. 2022, Accessed: Apr. 13, 2026. [Online]. Available: https://journalofcomputerengineering.com/index.php/jce/article/view/1509

Abstract

There is a controversial concept among many studies whether neonatal seizures are risk factors for neonatal death and/or neurodevelopment impairments (in case of newborn survivors). Multiple factors have been analyzed in literature, including perinatal factors, etiology factors, seizures characteristics factors, investigations findings factors, therapy-related factors. This paper aims to review the characteristics and the application context of different computational models developed for identifying both the risk factor of morbidity (epilepsy, cerebral palsy, development disability or their combination) and the mortality outcome after neonatal seizures. Consequently, we determined the groups of main risk factors using factor analysis. The vast majority of identified models are logistic regression models, but also decision tree models. In the literature, there is a large variation in establishing the risk factors determining poor or favorable outcome after a neonatal seizure, with similarities and inconsistencies. These findings could be a consequence of different approaches regarding inclusion criteria, methodologies used to identify seizure, seizures definition or description, analysis using computational models.
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Copyright (c) 2022 University College London (UCL), United Kingdom. (Author)