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Authors: Andreia Brandão ; Eliana Pereira ; Filipe Portela ; Manuel Santos ; António Abelha and José Machado

Affiliation: University of Minho, Portugal

ISBN: 978-989-758-074-1

Keyword(s): Data Mining, Intelligent Decision Support Systems, Voluntary Interruption of Pregnancy, Business Intelligence, Technology Acceptance.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Computational Intelligence ; Data Mining ; Databases and Information Systems Integration ; Enterprise Information Systems ; Evolutionary Computing ; Industrial Applications of AI ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Sensor Networks ; Signal Processing ; Soft Computing ; Symbolic Systems

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%.

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Paper citation in several formats:
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

@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},
}

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

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