Predicting Cardiovascular Disease as a Long-Term Diabetes Complication using SOM

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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.




Rajathi*, K., Jeyarani, R. A., … Vahini, M. Vi. (2020). Predicting Cardiovascular Disease as a Long-Term Diabetes Complication using SOM. International Journal of Recent Technology and Engineering (IJRTE), 8(6), 3288–3292.

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