Predicting Cardiovascular Disease as a Long-Term Diabetes Complication using SOM
K. Rajathi1, R. Asmetha Jeyarani2, K. Blessing Christiana3, T. Vijaya Vahini4
1K. Rajathi*, Associate Professor, Department of CSE, Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology, Chennai, India.
2R. Asmetha Jeyarani, Assistant Professor, Department of CSE, Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology, Chennai, India.
3K. Blessing Christiana, Assistant Professor, Department Deparment of IT, New Prince Shri Bhavani College of Engineering & Technology, Chennai, India.
4Ms VIjaya Vahini, Department of CSE, Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology, Chennai, India.
Manuscript received on March 12, 2020. | Revised Manuscript received on March 25, 2020. | Manuscript published on March 30, 2020. | PP: 3288-3292 | Volume-8 Issue-6, March 2020. | Retrieval Number: F8532038620/2020©BEIESP | DOI: 10.35940/ijrte.F8532.038620
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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: Cardiovascular disease (CVD) is the most common serious of long term type2 diabetic’s mellitus. It is estimated that most of the T2DM patients causes death due to CVD. Around 90% of CVD can be prevented with proper prediction of diabetes. Type 2 diabetes mellitus begins with insulin resistance, a condition in which it fails to respond to insulin properly. This paper explores Hybrid Wavelet Neural Network to train the system to learn the pattern to predict the disease and Self Organized map method is used for information clustering and visualization of excessive dimensional records to predict the disease with less parameter high accuracy which can help to prevent the disease. Modified Teaching Learning Based Optimization algorithm achieves the optimized learning from the pertained network. Teaching and learning based optimized technique yield better accuracy with a dataset of 770 patients. The measure of accuracy is compared with other algorithms and it is analyzed for further ratification.
Keywords: Cardiovascular (CVD), Type2 Diabetes Mellitus (T2DM), Self-Organized Mapping (SOM), Hybrid Wavelet Neural Network, Modified Teaching Learning Based Optimization.
Scope of the Article: Discrete Optimization.