ISBN: 978-981-11-0008-6 DOI: 10.18178/wcse.2016.06.059
Knowledge Discovery on Dengue Patients Using Data Mining Techniques
Abstract— Dengue fever represents the leading cause of deaths in Thailand. The statistical data obtained
from Ministry of Public Health, Thailand reveals that there are 60,000 dengue patients in 2015. Several
questions from Thai physicians are investigated using data mining techniques.This paper presents the
research work related to knowledge discovery using data mining technique. The objective is to analyze data
obtained from Dengue fever patients in Thailand in order to know the set of indicators that can classify the
Dengue severity. Some important markers such as the size of grown liver, the level of Aspartate
aminotransferase and Alanine aminotransferase are studied. The decision tree, fuzzy logic and Apriori
algorithms are applied to discover new knowledge. The performance of data mining techniques are compare
with World Health Organization criteria.
Index Terms— data mining, decision tree, fuzzy logic, Apriori
Nuanwan Soonthornphisaj, Daranee Thitiprayoonwongse
Department of Computer Science, Faculty of Science, Kasetsart University, THAILAND
Cite: Nuanwan Soonthornphisaj, Daranee Thitiprayoonwongse, "Knowledge Discovery on Dengue Patients Using Data Mining Techniques," Proceedings of 2016 6th International Workshop on Computer Science and Engineering, pp. 371-375, Tokyo, 17-19 June, 2016.