APPLICATION OF DECISION TREES IN THE PREDICTION OF DISEASE CASES IN TRADITIONAL MEDICINE

Traditional medicine is a source of health care accessible and affordable in Africa. It includes the traditional knowledge that meet primary health care needs. This knowledge based on experience is not structured and is filled with rigid and inadequate data that often lead to uncertainties and fatal errors. In this article, an ontology based on the knowledge of traditional medicine is developed. Thus, we propose a methodology to build a decision tree that corrects inaccuracies of traditional medicine. This consideration is based on the idea of probabilistic allocation of objects in different nodes of the tree based on a cut-off criterion. This is classification of diseases based on symp-toms. This work is a big step forward in the use of Semantic Web technologies, illustrated by a concrete case modeled and tested with a diagnostic problem in the case of traditional medicine.