Abstract

Diabetes mellitus type 2 has become one of the major causes of premature diseases and death in many countries. It accounts for the majority of diabetes cases around the world. Thus, we need to develop a system that diagnoses type 2 diabetes. In this thesis, a fuzzy expert system is proposed using the Mamdani fuzzy inference system to diagnose type 2 diabetes effectively. In order to evaluate the performance of our system, a comparative study has been initiated, and will contrast the proposed system with data mining algorithms, namely J48 Decision tree, multilayer perceptron, support vector machine, and Naïve Bayes. The developed fuzzy expert system and the data mining algorithms are validated with real data from the UCI machine learning datasets. Moreover, the performance of the fuzzy expert system is evaluated by comparing it to related work that used the Mamdani inference system to diagnose the incidence of type 2 diabetes. Alternate title: Comparative analysis of data mining algorithms for diagnosis Type 2 Diabetes

Highlights

  • INTRODUCTIONDiabetes is a chronic disease that occurs when the pancreas cannot produce enough insulin or when the body does not use the insulin effectively

  • Several common data mining algorithms, namely J48, multilayer perceptron (MLP), logistic regression, support vector machine (SVM), and Naïve Bayes are implemented using the Weka software. These algorithms and our proposed fuzzy expert system are applied to the Pima Indian Diabetes Dataset (PIDD) in order to measure the performance of our system and compare it with wellknown machine learning and statistical algorithms, a comparative analysis is done between our fuzzy expert system and a fuzzy expert system proposed in related work to evaluate the performance of our proposed system

  • 4.1 Dataset In order to compare and validate the findings, the system is tested on the most commonly used Pima Indian diabetes dataset [53], which belongs to the National Institute of Diabetes and Digestive and Kidney Diseases

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Summary

Introduction

Diabetes is a chronic disease that occurs when the pancreas cannot produce enough insulin or when the body does not use the insulin effectively. It is a major cause of heart attacks, kidney failure, blindness, lower limb amputation and strokes. In 2014, 422 million people were diagnosed with diabetes compared to 108 million people in 1980. It has been reported that an estimated 1.5 million deaths were directly caused by diabetes and that high blood glucose was the direct cause of 2.2 million deaths in 2012 [1]. The World Health Organization estimates that diabetes will be the 7th leading cause of death in 2030 [2].

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