Data Mining in Healthcare to Predict Cesarean Delivery Operations using a Real Dataset

Mona Jamjoom

2020

Abstract

In the digital era, the data revolution has become a significant part of every sector in society. The healthcare sector is one of the most vital parts of this revolution, as a massive amount of data is available, making medical case-related decisions critical. Hence, data-mining (DM) techniques are utilized to extract vital information and knowledge for decision-making. This study analysed data from cesarean delivery cases. A cesarean delivery operation generally takes place when there are challenges to normal delivery for several reasons or where normal delivery could cause potential complications in the future. In this paper, we have empirically examined several data-mining techniques for predicting the safest delivery type for both mother and child, using real cases taken from a health center in Tabriz. In addition, we used a cross-validation (CV) approach to evaluate the applied prediction models to ensure more realistic and reliable results. The naïve Bayesian (NB) classifier outperformed the other selected classifiers, with an accuracy rate of 65%. Available cesarean delivery operation data are rare, and increasing the cesarean case data is essential for better prediction.

Paper Citation

in Harvard Style

Jamjoom M. (2020). Data Mining in Healthcare to Predict Cesarean Delivery Operations using a Real Dataset.In Proceedings of the 1st International Conference on Computing and Emerging Sciences - Volume 1: ICCES, ISBN 978-989-758-497-8, pages 20-26. DOI: 10.5220/0010366700200026

in Bibtex Style

@conference{icces20,
author={Mona Jamjoom},
title={Data Mining in Healthcare to Predict Cesarean Delivery Operations using a Real Dataset},
booktitle={Proceedings of the 1st International Conference on Computing and Emerging Sciences - Volume 1: ICCES,},
year={2020},
pages={20-26},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010366700200026},
isbn={978-989-758-497-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Computing and Emerging Sciences - Volume 1: ICCES,
TI - Data Mining in Healthcare to Predict Cesarean Delivery Operations using a Real Dataset
SN - 978-989-758-497-8
AU - Jamjoom M.
PY - 2020
SP - 20
EP - 26
DO - 10.5220/0010366700200026