Published 30 APR 2019 •  vol 125  • 



Bhanu Prakash Doppala, Department of Computer Science and Multimedia, Lincoln University College, Malaysia
Divya Midhunchakkaravarthy, Department of Computer Science and Multimedia, Lincoln University College, Malaysia
Debnath Bhattacharyya, Department of Computer Science and Engineering, Vignan’s Institute of Information Technology, India



Problems related to heart is one of the fundamentally developing issue throughout the globe, prompting a large portion of deaths because of heart issues. The weight of cardiovascular sickness can be enhanced via hazard disease and accordingly essential counteractive action is an imperative need for all engineers of well-being arrangement. For every heart based diseases we need to undergo different medical examinations which kills lot of time to detect the exact root cause, rather than going for several diagnosis mechanisms. In this paper we propose that with limited parameters from the diagnosis results we can identify the issue of Cardiomegaly at early stages.



Heart disease, Prediction, Cardiomegaly, Healthcare, Classification, and Recurrent Fuzzy Neural Network (RFNN)



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Doppala, B. P., Midhunchakkaravarthy, D. & Bhattacharyya, D. (2019). Early Stage Detection of Cardiomegaly: An Extensive Review. International Journal of Advanced Science and Technology (IJAST), ISSN: 2005-4238(Print); 2207-6360 (Online), NADIA, 125, 13-24. doi: 10.33832/ijast.2019.125.02.

Doppala, Bhanu Prakash, et al. “Early Stage Detection of Cardiomegaly: An Extensive Review.” International Journal of Advanced Science and Technology, ISSN: 2005-4238(Print); 2207-6360 (Online), NADIA, vol. 125, 2019, pp. 13-24. IJAST, http://article.nadiapub.com/IJAST/Vol125/2.html.

[1] B. P. Doppala, D. Midhunchakkaravarthy, and D. Bhattacharyya, “Early Stage Detection of Cardiomegaly: An Extensive Review.” International Journal of Advanced Science and Technology (IJAST), ISSN: 2005-4238(Print); 2207-6360 (Online), NADIA, vol. 125, pp. 13-24, Apr 2019.