I.J. Information Technology and Computer Science, 2015, 10, 84-91 Published Online September 2015 in MECS (http://www.mecs-press.org/) DOI: 10.5815/ijitcs.2015.10.10 Copyright © 2015 MECS I.J. Information Technology and Computer Science, 2015, 10, 84-91 Improving the Prediction Rate of Diabetes using Fuzzy Expert System Vaishali Jain Department of CSE & IT, ITM University, Gurgaon-122017, India E-mail: vaishalijain.v@gmail.com Supriya Raheja Department of CSE & IT, ITM University, Gurgaon-122017, India E-mail: supriya@itmindia.edu Abstract—The use of fuzzy logic in disease diagnosis is very common and beneficial as it incorporates the knowledge and experience of physician into fuzzy sets and rules. Most of the research proposed different systems for the diabetes diagnosis. But their accuracy of prediction is not accurate. So, the proposed system presents promising approach for accurately predicting the diabetes by considering the different parameters which are helpful in the diagnosis of diabetes. The proposed fuzzy verdict mechanism takes the information collected from the patients as inputs in the form of datasets. System considers both rules and physicians knowledge to provide the prediction rate of diabetes. Evaluation shows the approach results in better accuracy as compared to other prediction approaches. Index Terms—Fuzzy Logic, Fuzzy Verdict Mechanism, Expert System, Fuzzy Logic based Diabetes Diagnosis System (FLDDS). I. INTRODUCTION Diabetes is a very common disease nowadays among the people of all age groups and has become a major health problem. With the rise in cases of diabetic patients there is a need of a reliable and accurate system that can diagnose the diabetes with a great accuracy at its early stage. The medical diagnosis of disease involves the patterns of observable symptoms and the result of diagnosis reports of test. But various costs and risks are associated with these tests. Various techniques and different systems have been proposed by the researchers to diagnose the diabetes, but the accuracy and efficiency of the prediction of diabetes is not so significant. All the developed expert systems aimed to diagnose the diabetes based on some parameters but there are some other parameters that had not been discussed so far. The existing systems have various drawbacks like some were used for a particular type of dataset, some needed dataset of good quality. Therefore there is a need of a system of good quality that considers all the parameters, uses the best technique and predicts the diabetes with greater accuracy. Fuzzy logic and expert system are important and very promising techniques in medical environment as it incorporates the knowledge and experience of physician and based on that information the system will predict the diabetes. With the help of fuzzy rule-based system we can avoid cost of conducting the test for the diabetes diagnosis. The proposed system solves the problem by selecting a subset of useful feature from a set of features. It also proves to improve the diagnosis accuracy using fuzzy rule-based classification system and by selecting important and useful features. This paper consists of seven sections. First section explains the introduction of this paper. In the second section the detailed problem of diabetes is discussed with its types. Third section deals with the fuzzy concept which includes fuzzy sets, their operations and fuzzy inference system. Fourth section discusses the related work in the field of fuzzy logic in medicine, diabetes diagnosis and blood pressure regulation. Fifth section is related to the proposed work in which we have discussed the architecture of proposed system, used dataset, fuzzy verdict mechanism and proposed algorithm. Sixth section shows the experimental results and the fuzzy rules used in the system. Finally seventh section describes the conclusion on which we have arrived and the last section of this paper shows the references which we have taken for this paper. II. DIABETES Diabetes is also known as Diabetes Mellitus in medical terms. In diabetes the blood sugar level abnormally gets high over a long period of time due to grouping of metabolic diseases. Due to high blood sugar patient complains the problem of frequent urination, increased hunger, and increased thirst. When the disease progresses, low amount of insulin is developed in the body which results in the less absorption of glucose by the cells. As a result blood glucose level is increased. When glucose is unabsorbed by the cells, it remains in the blood stream and kidneys needs to filter more glucose, but there is a limit to the amount of glucose kidney can filter. As a result more glucose is passed in the urine. Since glucose