Prediction of Glucose Concentration in Blood Plasma with Support Vector Regression Algorithm
Shanthi S
Shanthi S, Professor, Department of Electronics and Communication Engineering, Saveetha University, Chennai (Tamil Nadu), India.
Manuscript received on 16 August 2019 | Revised Manuscript received on 28 August 2019 | Manuscript Published on 06 September 2019 | PP: 352-355 | Volume-8 Issue- 6S, August 2019 | Retrieval Number: F10740886S19/19©BEIESP | DOI: 10.35940/ijeat.F1074.0886S19
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© 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: Diabetes Mellitus is due to the disorder of glucose metabolism because of defects in insulin secretion or insulin action. It has become a major health challenge nowadays. Monitoring and regulation of blood glucose is inevitable to avoid diabetic complications. Prediction of near future glucose levels and giving alert for appropriate action could be done by machine learning techniques. This would greatly assist the diabetes patients in the daily management of diabetes. This paper discusses the effectiveness of Support Vector Regression in diabetes management. The methodology has been applied to three different data sets and performance measure is analyzed with Root Mean Square Error values.
Keywords: Diabetes Mellitus, Blood Glucose Prediction, Machine Learning, Support Vector Regression.
Scope of the Article: Algorithm Engineering