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Applied Computing in Medicine and Health by Carol Oliver, Conor Mallucci, Abir Hussain, Dhiya Al-Jumeily

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Chapter 6

Prediction of Intrapartum Hypoxia from Cardiotocography Data Using Machine Learning

Paul Fergus1, De-Shuang Huang2,  and Hani Hamdan3     1Applied Computing Research Group, Liverpool John Moores University, Liverpool, UK     2Institute of Machine Learning and Systems Biology, Tongji University, Shanghai City, China     3CentraleSupélec, L2S UMR CNRS 8506, Gif-sur-Yvette, FranceE-mail: p.fergus@ljmu.ac.uk, dshuang@tongji.edu.cn, Hani.Hamdan@centralesupelec.fr

Abstract

Uterine contractions produced during labor have the potential to damage a fetus by diminishing the maternal blood flow to the placenta, which can result in fetus hypoxia. In order to observe this phenomenon in practice, labor and delivery are routinely monitored using cardiotocography ...

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