Fetal electrocardiogram prediction using machine learning: a random forest-based approach
Mohammed Moutaib,
Mohammed Fattah,
Yousef Farhaoui
et al.
Abstract:<p class="IOPText">Monitoring fetal health during pregnancy ensures safe delivery and the newborn’s well-being. The fetal electrocardiogram (fetal ECG) is a valuable tool for assessing fetal cardiac health, but interpretation of ECG data can be challenging due to its complexity and variability. In this work, we explore the application of machine learning, particularly random forest, to predict and analyze fetal ECGs. With its ability to manage large datasets and provide precise insights, random forest is… Show more
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