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)
[1] Kenney, M. & Zysman, J. (2016). The rise of the platform economy. Issues in Science and Technology, 32(3), 61.
[2] LathaParthiban and R.Subramanian,"Intelligent Heart Disease Prediction System using CANFIS and Genetic Algorithm",World Academy of Science, Engineering and TechnologyInternational Journal of Medical and Health Sciences Vol: 1, No: 5, 2007,PP 1-2.
[3] U.Sinha, U.S.Sahay, S.A.Athavale, R.Deopujari and S.Kumar,"comparative study of cardiac size by chest X-ray and echocardiography",Journal of the Anatomical Society of India 62 (2013),PP 28-32.
[4] SnehaNikam, Priyanshi Shukla and MeghShah,"Cardiovascular Disease Prediction Using Genetic Algorithm and Neuro fuzzy System",International Journal of Latest Trends in Engineering and Technology Vol.(8)Issue(2), PP108-109.
[5] AnimeshHazra, Subrata Kumar Mandal, Amit Gupta, Arkomita Mukherjee and AsmitaMukherjee,"Heart Disease Diagnosis and Prediction Using Machine Learning and Data Mining Techniques:AReview",Advances in Computational Sciences and Technology ISSN 0973-6107 Volume 10, Number 7 (2017), PP 20-23.
[6] KiyanaZolfaghar, NarenMeadem, AnkurTeredesai, BrianMuckian and SenjutiBasuRoy,"Big Data Solutions for Predicting Risk-of-Readmission for Congestive Heart Failure Patients", 2013 IEEE International Conference on Big Data, PP 65-67.
[7] RuchaShinde, Sandhya Arjun, Priyanka Patil, Prof.JaishreeWaghmare,"An Intelligent Heart Disease Prediction System Using K-Means Clustering and Naive Bayes Algorithm",International Journal of Computer Science and Information Technologies, Vol. 6 (1) , 2015,PP 637-638.[7]Harmeet S Chana, Clarie A Martin, Holly E Cakebread, Felicia D adjei and Parag R Gajendragadkar ,"Diagnostic accuracy of cardiothoracic ratio on admission chest radiography to detect left or right ventricular systolic dysfunction: a retrospective study",Journal of the Royal Society of Medicine; 2015, Vol. 108(8),PP 2-4.
[8] Y. B. Mensah, K. Mensah, S. Asiamah, H. Gbadamosi, E. A. Idun, W.Brakohiapa and A. Oddoye,"Establishing The Cardiothoracic Ratio Using Chest Radiographs In An Indigenous Ghanian Population: A Sample Tool For Cardiomegaly Screening”, Ghana Medical Journal Volume 49, Number 3 September 2015, PP 160-162.
[9] Kaan Uyar and Ahmet Ilhan, “Diagnosis of heart disease using genetic algorithm based trained recurrent fuzzy neural networks”, ICSCCW, 22-23 August 2017, Budapest, Hungary. PP 590-592.
[10] Vincy Cherian and BinduM.S,"Heart Disease Prediction using Naive Bayes Algorithm and Laplace smoothing technique neural networks",9th International Conference on Theory and Application of Soft Computing,", International Journal of Computer Science Trends and Technology (IJCST) – Volume 5 Issue 2, Mar – Apr 2017, PP 68-70.
[11] Leszczynskakatarzyna, Chojnikimaciej, Haponiukireneusz, preis Krzysztof and GerratHaponiokKatarzyna, “The Rare Reason of Fatal Cardiomegaly-Prenatal Diagnosis of Vein of Galen Aneurysmal Malformation”, Biomed J Sci& Tech Res Volume 5- Issue 5: 2018, PP 1-2.
[12] https://www.researchgate.net/figure/Age-distribution-of-respondents-with-cardiomegaly_fig1_272088967 [Last Referred on 11.03.2019].
[13] https://www.healtheuniversity.ca/en/cardiaccollege/Disease/How_The_Heart_Works/Pages/irregular-beats.aspx[Last Referred on 11.03.2019].
[14] https://www.lorisangels.com/single-post/2015/10/15/Tips-for-Dealing-with-Edema-Caused-by-Congestive-Heart-Failure-CHF [Last Referred on 11.03.2019].
[15] https://www.impella.com/blog/is-an-echocardiogram-right-for-me/ [Last Referred on 11.03.2019].
[16] https://www.sciencephoto.com/media/317066/view/healthy-heart-mri[Last Referred on 11.03.2019]
APA:
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.
MLA:
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.
IEEE:
[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.
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