15Dec 2019

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

  • Research professor at The University of Felix Houphouet - Boigny, Cote dIvoire
  • Research professor at The Virtual University of Cote dIvoire
  • Research professor The University of Peleforo Gon Coulibaly, Cote dIvoire
  • Research professor The Virtual University, Cote dIvoire
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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.


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[T. Issa , N Guessan Behou Gerard, Achiepo Odilon and Kouame Euloge (2019); APPLICATION OF DECISION TREES IN THE PREDICTION OF DISEASE CASES IN TRADITIONAL MEDICINE Int. J. of Adv. Res. 7 (12). 207-212] (ISSN 2320-5407). www.journalijar.com


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Article DOI: 10.21474/IJAR01/10145       DOI URL: http://dx.doi.org/10.21474/IJAR01/10145


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