Prevalence of Diabetes Mellitus in Tiruchirappalli District using Machine Learning
L. Arockiam1, S. Sathyapriya2, V.A. Jane3, A. Dalvin Vinoth Kumar4 

1Dr. L. Arockiam, Associate Professor. Department of Computer Science, St. Joseph’s College (Autonomous), Trichy-2.
2S. Sathyapriya, Ph. D Scholar, Department of Computer Science, St. Joseph’s College (Autonomous), Trichy-2.
3V.A. Jane, Ph.D Scholar, Department of Computer Science, St. Joseph’s College (Autonomous), Trichy-2.
4A. Dalvin Vinoth Kumar, Assistant Professor, REVA University, Bangalore.

Manuscript received on 08 March 2019 | Revised Manuscript received on 15 March 2019 | Manuscript published on 30 July 2019 | PP: 6400-6403 | Volume-8 Issue-2, July 2019 | Retrieval Number: B2219078219/19©BEIESP | DOI: 10.35940/ijrte.B2219.078219
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Abstract: Machine learning is a part of AI which develops algorithms to learn patterns and make decision form the massive data. Recently, Machine learning has been used to resolving various critical medical problems. Diabetes is one of the dangerous disease, which can lead to more complicated, including deaths if not timely treated. The study is designed for providing the prevalence of Diabetes Mellitus in Tiruchirappalli district using machine learning algorithms and it was detected that the polluted air causes diabetes disease and also increases the risk of that disease. This proposed work helps the people in preventing diabetes disease using various diabetic attributes with an aim to enhance the quality of healthcare and lessen the diagnoses cost of the disease. In future, the work done may be extended by considering many other attributes and by implementing it through various algorithms to improve the prediction accuracy of diabetes mellitus.
Index Terms: Diabetes Mellitus, Machine Learning, Prediction, WEKA.

Scope of the Article: Machine Learning