Classification of Cardiotocography Records with Naïve Bayes

Year 2019, Volume: 3 Issue: 2, 105 - 110, 31.12.2019

Emre Avuçlu , Abdullah Elen

Abstract

Cardiotocography provides information about the fetal heart rate during pregnancy and childbirth, monitoring the uterine contractions and the physiological status of the fetus to identify hypoxia. Accurate information from these records can be used to estimate the pathological condition of the fetus. Thus, it allows early intervention by reporting any irreversible negative condition in the fetus. In this study, due to the importance of this subject, Naive Bayes machine learning algorithm can be used to diagnose the model developed. The result was 97.18% classification and 95.68% test success with Naive Bayes machine learning algorithm. The obtained data were presented in detail in the following sections.

Keywords

Biomedical diagnostics, Machine learning algorithms, Fetal heart rate measurements

Classification of Cardiotocography Records with Naïve Bayes

Abstract

Cardiotocography provides information about the fetal heart
rate during pregnancy and childbirth, monitoring the uterine contractions and
the physiological status of the fetus to identify hypoxia. Accurate information
from these records can be used to estimate the pathological condition of the
fetus. Thus, it allows early intervention by reporting any irreversible
negative condition in the fetus. In this study, due to the importance of this
subject, Naive Bayes machine learning algorithm can be used to diagnose the
model developed. The result was 97.18% classification and 95.68% test success
with Naive Bayes machine learning algorithm. The obtained data were presented
in detail in the following sections.

Keywords

Biomedical diagnostics, Machine learning algorithms, Fetal heart rate measurements.

References

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