Fetal and Maternal Electrocardiogram ECG Prediction using Convolutional Neural Networks

Mohammed Moutaib, Mohammed Fattah, Yousef Farhaoui, Badraddine Aghoutane and Moulhime El Bekkali

Data and Metadata, 2023, vol. 2, 113

Abstract: Predicting fetal and maternal electrocardiograms (ECGs) is crucial in advanced prenatal monitoring. In this study, we explore the effectiveness of Convolutional Neural Networks (CNNs), using a carefully developed methodology to predict the category of fetal (F) or maternal (M) ECGs. In the first part, we trained a CNN model to predict fetal and maternal ECG images. In the following sections, the study results will be revealed. The CNN model demonstrated its ability to effectively discriminate between fetal and maternal patterns using automatically learned features

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:dbk:datame:v:2:y:2023:i::p:113:id:1056294dm2023113

DOI: 10.56294/dm2023113

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