Early prediction of type 2 diabetes using fuzzy logic

In the first chapter of this master's thesis, which consists of four chapters, fuzzy sets and the historical development of fuzzy logic are introduction. In the second chapter, the fundamentals of fuzzy set theory, operations on fuzzy sets and types of the membership functions are given. In the third chapter, it is aimed to predict type 2 diabetes early in the Matlab graphical development platform. For the designed system, the data of patients diagnosed with type 2 diabetes and healthy individuals were used by taking expert opinion. While designing the Decision Support system, waist/hip ratio and waist circumference and waist circumference/height ratios were used as inputs to determine Type 2 diabetes risk assessment. In this design, Mamdani type fuzzy sets were created by using triangular and trapezoidal membership functions, which provide a smoother transition. For the output of the system, fuzzy logic membership functions are created and a fuzzy output is produced. The last chapter is the conclusion chapter of the thesis.