Performance Evaluation od Predictive Classifiers for Pregnancy Care
Published in: 2016 IEEE Global Communications Conference (GLOBECOM)
Date of Conference: 4-8 Dec. 2016
Date Added to IEEE Xplore: 06 February 2017
ISBN Information:
INSPEC Accession Number: 16654639
Publisher: IEEE
Conference Location: Washington, DC, USA
Abstract:
Hypertensive disorders are the leading cause of deaths during pregnancy. Risk pregnancy accompaniment is essential to reduce these complications. Decision support systems (DSS) are important tools to patients’ accompaniment. These systems provide relevant information to health experts about clinical condition of the patient anywhere and anytime. In this paper, a model that uses the Naive Bayesian classifier is introduced and its performance is evaluated in comparison with the Data Mining (DM) classifier named J48 Decision Tree. This study includes the modeling, performance evaluation, and comparison between models that could be used to assess pregnancy complications. Evaluation analysis of the results is performed through the use of Confusion Matrix indicators. The founded results show that J48 decision tree classifier performs better for almost all the used indicators, confirming its promising accuracy for identifying hypertensive disorders on pregnancy.
MAURO OLIVEIRA - Aracati D.C. , Canoa Quebrada City 