Machine learning models based on clinical indices and cardiotocographic features for discriminating asphyxia fetuses—Porto retrospective intrapartum study

Machine learning models based on clinical indices and cardiotocographic features for discriminating asphyxia fetuses—Porto retrospective intrapartum study

IntroductionPerinatal asphyxia is one of the most frequent causes of neonatal mortality, affecting approximately four million newborns worldwide each year and causing the death of one million individuals. One of the main reasons for these high incidences is the lack of consensual methods of early di...

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Bibliographic Details
Main Authors: Maria Ribeiro, Inês Nunes, Luísa Castro, Cristina Costa-Santos, Teresa S. Henriques
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-03-01
Series:Frontiers in Public Health
Subjects:
non-linear methods
neonatology
fetal heart rate
cardiotocography
perinatal asphyxia
Online Access:https://www.frontiersin.org/articles/10.3389/fpubh.2023.1099263/full

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https://www.frontiersin.org/articles/10.3389/fpubh.2023.1099263/full

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