A FRAMEWORK FOR ONTOLOGY- BASED DIABETES DIAGNOSIS USING BAYELSIAN OPTIMIZATION TECHNIQUE

Authors

  • F. M. OKIKIOLA Department of Computer Technology, Yaba College of Technology, Lagos
  • O. S. ADEWALE 2Department of Computer Science, Federal University of Technology, Akure, Ondo State
  • A. M. MUSTAPHA Department of Computer Science, Federal University of Agriculture, Abeokuta, Nigeria
  • A. M. IKOTUN Department of Computer Technology, Yaba College of Technology, Lagos
  • O. L. LAWAL Department of Computer Technology, Yaba College of Technology, Lagos.

DOI:

https://doi.org/10.51406/jnset.v17i1.1906

Keywords:

Diabetes, Ontology, Bayesian Classifiers, Knowledge Management, Diagnosis Management

Abstract

Diabetes Management System (DMS) is a computer-based system which aid physicians in properly diagnosing diabetes mellitus disease in patients. The DMS is essential in making individuals who have diabetes aware of their state and type. Existing approaches employed have not been efficient in considering all the diabetes type as well as making full prescription to diabetes patients. In this paper, a framework for an improved Ontology-based Diabetes Management System with a Bayesian optimization technique is presented. This helped in managing the diagnosis of diabetes and the prescription of treatment and drug to patients using the ontology knowledge management. The framework was implemented using Java programming language on Netbeans IDE, Protégé 4.2 and mysql. An extract of the ontology graph and acyclic probability graph was shown. The result showed that the nature of Bayesian network which has to do with statistical calculations based on equations, functions and sample frequencies led to more precise and reliable outcome.

 

 

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Published

2019-11-06

Issue

Vol. 17 No. 1 (2018)

Section

Articles