ENHANCED PREDICTIVE MODEL FOR SCHISTOSOMIASIS

Neglected Tropical Diseases (NTDs) are wide spread diseases found in many countries Africa, Asia and Latin America, they mostly tropical areas where people have no access to clean water or safer ways dispose of human waste. Schistosomiasis is one the NTDs. Data mining used extracting rules predict certain information Information Technology, medical science, biology, education, resources. Classification techniques mining. In this work, we three classifiers namely; Naïve Bayes, Support Vector Machine Logistic Regression design a framework for classifying predicting status its complications suspected patient using their clinical data. For purpose study, considered parameters: Abdominal, Diarrhea, Bloody_stool, Bloody urine, Swim, Dam_river_ use, Urinating_stool_in_water, Boil_water_use. The was trained data acquired from Federal Medical Centre Katsina NTD unit State ministry health, test performance accuracy. research shown that out classifiers, performed better by having 97.8%