Predicting the Risk Associated to Pregnancy using Data Mining

Andreia Brandão, Eliana Pereira, Filipe Portela, Manuel Santos, António Abelha, José Machado

2015

Abstract

Woman willing to terminate pregnancy should in general use a specialized health unit, as it is the case of Maternidade Júlio Dinis in Porto, Portugal. One of the four stages comprising the process is evaluation. The purpose of this article is to evaluate the process of Voluntary Termination of Pregnancy and, consequently, identify the risk associated to the patients. Data Mining (DM) models were induced to predict the risk in a real environment. Three different techniques were considered: Decision Tree (DT), Support Vector Machine (SVM) and Generalized Linear Models (GLM) to perform the classification task. Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology was applied to drive this work. Very promising results were obtained, achieving a sensitivity of approximately 93%.

Paper Citation

in Harvard Style

Brandão A., Pereira E., Portela F., Santos M., Abelha A. and Machado J. (2015). Predicting the Risk Associated to Pregnancy using Data Mining . In Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-074-1, pages 594-601. DOI: 10.5220/0005286805940601

in Bibtex Style

@conference{icaart15,
author={Andreia Brandão and Eliana Pereira and Filipe Portela and Manuel Santos and António Abelha and José Machado},
title={Predicting the Risk Associated to Pregnancy using Data Mining},
booktitle={Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2015},
pages={594-601},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005286805940601},
isbn={978-989-758-074-1},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Predicting the Risk Associated to Pregnancy using Data Mining
SN - 978-989-758-074-1
AU - Brandão A.
AU - Pereira E.
AU - Portela F.
AU - Santos M.
AU - Abelha A.
AU - Machado J.
PY - 2015
SP - 594
EP - 601
DO - 10.5220/0005286805940601