Expert System for Dengue Fever Prediction (ESDFP)

Abstract

Dengue is one of the most speedily increasing and an important public health issue in tropical and subtropical regions which sometimes causes continual epidemics. The general symptoms of dengue are fever which include joint pain, headache, vomiting etc.; however, if Dengue is not detected at an early stage and treated as normal fever then in severe cases, a patient may experience severe bleeding and shock, which may even lead to death. Thus, increasing Dengue Fever (DF) can be very severe and critical, turning out to be a global treat. So, considering the severity of DF, an intelligent expert system can be developed, named Expert System for Dengue Fever Prediction (ESDFP), based on symptomatic features to ascertain Dengue fever with high possibility before pathological test; thereby, ESDFP saves time and money for pathological diagnosis, and reduces life threatening risk by treating Dengue at an early stage. ESDFP takes physical symptoms, prepares the data in convenient form to process effectively and finally uses a condensed Decision Tree (DT) for DF classification. The performance of ESDFP is compared on basis of classification accuracy, precision, recall and F- measures with simple DT.