WCSE 2016
ISBN: 978-981-11-0008-6 DOI: 10.18178/wcse.2016.06.059

Knowledge Discovery on Dengue Patients Using Data Mining Techniques

Nuanwan Soonthornphisaj, Daranee Thitiprayoonwongse

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.