Cruz, A. and Tumibay, G. (2019) An Efficiency Assessment of Tuberculosis Treatment on Health Centers: A Data Envelopment Analysis Approach. Journal of Computer and Communications, 7, 11-20.
https://doi.org/10.4236/jcc.2019.74002

has been cited by the following article:

• TITLE: Predicting Tuberculosis Treatment Relapse: A Decision Tree Analysis of J48 for Data Mining

  AUTHORS: Arnold P. Dela Cruz, Gilbert M. Tumibay

  KEYWORDS: Data Mining, Decision Tree, J48, Tuberculosis, WEKA

  JOURNAL NAME: Journal of Computer and Communications, Vol.7 No.7, July 29, 2019

  ABSTRACT: Tuberculosis remains an important problem in public health that threatens the world, including the Philippines. Treatment relapse continues to place a severe problem on patients and TB programs worldwide. A significant reason for the development of decline is poor compliance with medical treatments. The objectives of this research are to generate a predictive data mining model to classify the treatment relapse of TB patients and to identify the features influencing the category of treatment relapse. The TB patient dataset is applied and tested in decision tree J48 algorithm using WEKA. The J48 model identified the three (3) significant independent variables (DSSM Result, Age, and Sex) as predictors of category treatment relapse.