International Research Journal of Engineering and Technology (IRJET) Volume: 04 Issue: 02 | Feb -2017
www.irjet.net
e-ISSN: 2395 -0056 p-ISSN: 2395-0072
Prediction of Diabetes Using Probability Approach T.monika Singh, Rajashekar shastry T. monika Singh M.Tech Dept. of Computer Science and Engineering , Stanley College of Engineering and Technology for Women, Telangana- Hyderabad, India. Dr.B.srinivasu Associate Professor Dept. of Computer Science and Engineering , Stanley College of Engineering and Technology for Women, Telangana- Hyderabad, India. Rajashker Shastry Assistant Professor Dept. of Computer Science and Engineering , Stanley College of Engineering and Technology for Women, Telangana- Hyderabad, India. ---------------------------------------------------------------------***--------------------------------------------------------------------Key Words: classification, Bayesian network,
Abstract – The discovery of knowledge from medical
attributes, prediction, probability.
datasets is important in order to make effective medical
1.INTRODUCTION
insulin is disturbed in the body which consequently leads to the
Data mining is the process of discovering correlations, patterns or relationships through large amount of data stored in repositories, databases and data warehouse. Thus, new tools and techniques are being developed to solve this problem through automation [1]. Many techniques or solutions for data mining and knowledge discovery in databases are very widely provided for classification, association, clustering and regression, search, optimization, etc. Health Informatics is a rapidly growing field that is concerned with applying computer science and information technology to medical and health data.
increase of glucose level in the blood. Using data mining
1.1 Diabetes
diagnosis. With the emerging increase of diabetes, that recently affects around 346 million people, of which more than one-third go undetected in early stage, a strong need for supporting the medical decision-making process is generated. Diabetes mellitus is a chronic disease and a major public health challenge worldwide. Diabetes is ascribed to the acute conditions under which the production and consumption of
Diabetes is a chronic disease that occurs when the human pancreas does not produce enough insulin, or when the body cannot effectively use the insulin it produces, which leads to an increase in blood glucose levels [2]. Generally a person is considered to be suffering from diabetes, when blood sugar levels are above normal. 1.1.1 Types of Diabetes The three main types of diabetes are described below: Type 1 – In this type of diabetes, the pancreatic cells that produce insulin have been destroyed by the defense system of the body. Type 2- In this case the various organs of the body become insulin resistant, and this increases the demand for insulin. Gestational diabetes – It is a type of diabetes that tends to occur in pregnant women due to the high sugar levels as the pancreas don’t produce sufficient amount of insulin. Controlling the blood glucose level of diabetic patients and keeping it within the normal range (70 mg/dL -120 mg/dL) is therefore the focal goal of physicians [3].
methods to aid people to predict diabetes has gain major popularity. In this project, Bayesian Network classifier was proposed to predict the persons whether diabetic or not. Bayesian networks are considered as helpful methods for the diagnosis of many diseases. They, in fact, are probable models which have been proved useful in displaying complex systems and showing the relationships between variables in a graphic way. The advantage of this model is that it can take into account the uncertainty and can get the scenarios of the system change for the evaluation of diagnosis procedures. The dataset used is Pima Indian Diabetes dataset, which collects the information of persons with and without diabetes.
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