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Research Article

Classification And Prediction Of Heart Disease From Diabetes Patients Using Hybrid Particle Swarm Optimization And Library Support Vector Machine Algorithm


Author(s): C.Kalaiselvi , G.M.Nasira
Affiliation: 1Research Scholar, Karpagam University, Coimbatore, Assistant professor and Head, Dept of Computer Applications, Tiruppur Kumaran College for Women, Tirupur, Tamilnadu
Year of Publication: 2015
Source: International Journal of Computing Algorithm
     
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Citation: C.Kalaiselvi, G.M.Nasira. "Classification And Prediction Of Heart Disease From Diabetes Patients Using Hybrid Particle Swarm Optimization And Library Support Vector Machine Algorithm." International Journal of Computing Algorithm 4.2 (2015): 54-58.

Abstract:
The multi-factorial chronicle, severe disease among human is diabetes. As a result of abnormal level of glucose in body leads to heart attack, kidney disease, renal failure, Hyperglycemia and also cancer in organs like liver and pancreas. Many studies have been proved that several types of heart diseases are possible in diabetic patients having a high blood sugar. Many approaches were proposed to diagnose both Diabetes and heart diseases. Most of the diabetes people can also have heart diseases called as Diabetic Cardiomyopathy.


Keywords Diabetes Mellitus, Cardio vascular, Cholesterol, Prediction, Blood Pressure


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@article{Cla1587955, author = {C.Kalaiselvi,G.M.Nasira}, title = {Classification And Prediction Of Heart Disease From Diabetes Patients Using Hybrid Particle Swarm Optimization And Library Support Vector Machine Algorithm}, journal={International Journal of Computing Algorithm}, volume={4}, issue={2}, issn = {2278-2397}, year = {2015}, publisher = {Scholarly Citation Index Analytics-SCIA}

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  • [2] Duckworth W and Abraira, “VADT Investigators: Glucose Control and VasculaComplications in Veterans with Type 2 Diabetes”, N Engl J Med 3602:129–139, 2009.
  • [3] Ford ES, Giles WH, Dietz WH. Prevalence of the metabolic syndrome among US adults: findings from the third National Health and Nutrition Examination Survey. JAMA 2002; 287:356 –9.
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  • [6] From AM, Leibson CL, Bursi F, et al. Diabetes in heart failure: prevalence and impact on outcome in the population. Am J Med, 119:591–9, 2006.
  • [7] AllamAppaRao Croft JB, Giles WH, Rashidee A. Hospitalization of patients with heart failure: National Hospital Discharge Survey, 137:352, 60, 2009.
  • [8] ShishirMurarka and Line iden Berge “Prevalence and characteristics of depressive disorder in type 1 diabetes”, BMC Research Notes, 6:543, 2-5, 2013.
  • [9] Loren E wold “Depressive Disorders among Michigan Adults by Diabetes Status”, depression and diabetes among Michigan adult, 6, 1-2, 2012.
  • [10] Ronald M. Witteles “Insulin resistant cardiomyopathy and heart failure” Journal of American College of cardiomyopathy, vol.2, 94-100, 2008.
  • [11] Xiaoyan Zhang and Richard E “Heart Failure in SAVOR-TIMI 53: The hindsight of diabetic retinopathy” Keenan research center Journal of diabetes, 2-10, 2014.
  • [12] Mohammed K. Ali “Diabetes & coronary heart disease: Current perspectives” Indian journal of medical research, 1325, 584–597, 2010.
  • [13] George L. Bakris “Preclinical diabetic cardiomyopathy: prevalence, screening and outcome” Internal Medicine University Department, 1-27, 2009.
  • [14] M.Harris “The role of primary health care in preventing the onset of chronic disease, with a particular focus on the lifestyle risk factors of obesity, tobacco and alcohol” Centre for Primary Health Care and Equity, UNSW, 1-21, 2008.
  • [15] Anderson KM “. Correlation of regional cardiovascular disease mortality in India with lifestyle and nutritional factors. Int J Cardiol 2006; 108: 291-300.

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