Paper Info
Title
Performance Evaluation of Predictive Classifiers for Pregnancy Care.
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.
Year
Venue
Keywords
2016
IEEE Global Communications Conference
e-Health,Hypertension,Decision support systems,Bayes methods,Decision trees,Data mining,Pregnancy
Field
DocType
ISSN
Decision tree,Data mining,Confusion matrix,Naive Bayes classifier,Computer science,Pregnancy,Decision support system,C4.5 algorithm,Artificial intelligence,Classifier (linguistics),Machine learning,Decision tree learning
Conference
2334-0983
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Mario W. L. Moreira1246.29
JOEL J. P. C. RODRIGUES23484341.72
Antonio M. B. Oliveira321.41
Kashif Saleem421421.58
Augusto Neto511424.44