Using Rule-Based Reasoning and Object-Oriented Methodologies to Diagnose Diabetes

Abstract

Problem statement: Diabetes mellitus or diabetes epidemic is one of the high prevalence diseases worldwide with increased number of disability, complications and death toll. An early diagnosis helps patients and medical practitioners to reduce the burden of diabetes. Approach: In this research, we propose a framework for a system using rule-based reasoning and object-oriented methodologies to diagnose both Type 1 and Type 2 diabetes. Results: Extensive literature reviews were carried out and questionnaires were distributed to medical practitioners to build the knowledge base. This knowledge base stores the rules needed to perform a diagnosis. Conclusion: This study only presents the proposed framework and not the system itself. We believe that great improvements can be provided to the medical practitioners and also the diabetics with the implementation of this system in future.