Prediction of Type 1 Diabetes Mellitus using Datamining Techniques
Dr. K. Saminathan*, Assistant Professor, Department of Computer Science, A.V.V.M Sri Pushpam College, Poondi.
Manuscript received on September 20, 2019. | Revised Manuscript received on October 15, 2019. | Manuscript published on October 30, 2019. | PP: 884-887 | Volume-9 Issue-1, October 2019 | Retrieval Number: A9400109119/2019©BEIESP | DOI: 10.35940/ijeat.A9400.109119
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Type1 diabetes is a sickness occurs when your immune system fighting against infection, affects and erode the insulin generating beta cells of the pancreas. In general, when the blood sugar stage increases, the pancreas makes more insulin. Insulin helps to go sugar out of the blood so it can be used for liveliness. Type 1 diabetes occurs due to the immune system which affects cells in the pancreas that make insulin. The pancreas cannot make adequate insulin, so the blood sugar level continues to increase. According to the children history of type 1 diabetes may enhance risk of their life. Type 1 diabetes cannot be cured, but it can be controlled and managed. In this study we use Naive Bayes, linear regression and k-means algorithm for data analysis and prediction. It predicts the diabetes affected children with maximum level of accuracy 96% by using of data mining algorithms.
Keywords: Type 1 Diabetes, Naive Bayes, Linear Regression, K-Means, Decision Stump.