Evaluation of Maturation in Preterm Infants Through an Ensemble Machine Learning Algorithm Using Physiological Signals

IEEE Journal of Biomedical and Health Informatics(2022)

引用 8|浏览21
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摘要
This study was designed to test if heart rate variability (HRV) data from preterm and full-term infants could be used to estimate their functional maturational age (FMA), using a machine learning model. We propose that the FMA, and its deviation from the postmenstrual age (PMA) of the infants could inform physicians about the progress of the maturation of the infants. The HRV data was acquired fro...
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关键词
Heart rate variability,Pediatrics,Statistics,Sociology,Genetic algorithms,Feature extraction,Machine learning
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