Diagnosis of Heart Disease using Cultural Algorithm with Neural Network

Authors

  • Shrivastava S Dept. of Computer Science & Engineering, IES-IPS Academy, RGPV, Indore, India
  • Shrivastava S Dept. of Computer Science & Engineering, IES-IPS Academy, RGPV, Indore, India

DOI:

https://doi.org/10.26438/ijcse/v6i9.486491

Keywords:

Back Propagation, Cardiovascular disease Confusion Matrix, Genetic Algorithm, Neural Network

Abstract

Heart disease detection is considered as the most complicated task in the world of medical sciences. There arises a necessity to progress the work and to develop a decision support system to find out a heart disease of a patient. To achieve a correct and cost effective treatment computer-based and support systems can be developed to make good decision. These information which exists contains the huge amounts of data which are organized in the form of images, text, charts and numbers. Hence, there is necessity which is motivating to create an excellent and useful project which will help physicians and cardiologists to predict the heart disease before it damage the health. It can be able to solve complicated enquiries for detecting heart disease in a patient and as a result it will assist medical practitioners to make more accurate and precise clinical decisions which traditional decision support systems were not able to decide. By providing effective and respective solution, it will surely help to reduce costs of treatment.

References

[1] Jones, D.S. and Greene, J.A., 2013. The decline and rise of coronary heart disease: understanding public health catastrophism. American journal of public health, 103(7), pp.1207-1218.

[2] Mathers, C.D. and Loncar, D., 2006. Projections of global mortality and burden of disease from 2002 to 2030. Plos med, 3(11), p.e442.

[3] World Health Organization, 2011. Global status report on noncommunicable diseases 2010. Geneva: World Health Organization.

[4] Buttar, H.S., Li, T. and Ravi, N., 2005. Prevention of cardiovascular diseases: Role of exercise, dietary interventions, obesity and smoking cessation. Experimental & Clinical Cardiology, 10(4), p.229.

[5] Jenkins, C.D., 1988. Epidemiology of cardiovascular diseases. Journal of consulting and clinical Psychology, 56(3), p.324.

[6] World Health Organization, 2007. Prevention of cardiovascular disease. World Health Organization.

[7] Cowie, M.R., Anker, S.D., Cleland, J.G., Felker, G.M., Filippatos, G., Jaarsma, T., Jourdain, P., Knight, E., Massie, B., Ponikowski, P. and López‐Sendón, J., 2014. Improving care for patients with acute heart failure: before, during and after hospitalization. ESC Heart Failure, 1(2), pp.110-145.

[8] Ajay, V.S. and Prabhakaran, D., 2010. Coronary heart disease in Indians: Implications of the INTERHEART study. The Indian journal of medical research, 132(5), p.561.

[9] Centre for Disease Control and Prevention, Online available at: http://www.cdc.gov/heartdisease/risk_factors.htm

[10] American Heart Association, Online available at: http://www.heart.org/HEARTORG/Conditions

[11] D. Isern, D. Sanchez, and A. Moreno, “Agents Applied in Health Care: A Review”, International Journal of Medical Informatics, Vol. 79, Issue 3, pp. 146-166, 2010.

[12] Syed Umar Amin, Kavita Agarwal, Dr. Rizwan Beg, “Genetic Neural Network Based Data Mining in Prediction of Heart Disease Using Risk Factors”, Proceedings of IEEE Conference on Information and Communication Technologies (ICT), pp. 1227–1231, April 2013.

[13] Reynolds, R.G., 1994, February. An introduction to cultural algorithms. In Proceedings of the third annual conference on evolutionary programming (Vol. 131139). Singapore.

[14] Reynolds, R.G. and Peng, B., 2004, November. Cultural algorithms: modeling of how cultures learn to solve problems. In Tools with Artificial Intelligence, 2004. ICTAI 2004. 16th IEEE International Conference on (pp. 166-172). IEEE.

[15] S. Sabeena, V. Sujitha “Prediction of Heart Disease Using AI and NLP Techniques”, International Journal of Computer Sciences and Engineering, Vol-6, Issue-2, Jan 2018

Downloads

Published

2018-09-30
CITATION
DOI: 10.26438/ijcse/v6i9.486491
Published: 2018-09-30

How to Cite

[1]
S. Shrivastava and S. Shrivastava, “Diagnosis of Heart Disease using Cultural Algorithm with Neural Network”, Int. J. Comp. Sci. Eng., vol. 6, no. 9, pp. 486–491, Sep. 2018.

Issue

Vol. 6 No. 9 (2018): IJCSE September Editor

Section

Research Article

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.