Early cardiac disease detection using neural networks

Hugo D. Calderon-Vilca; Kevin E.Chagua Callupe; Richard J.Inga Aliaga; Jair Barzola Cuba; Flor C. Marino-Cardenas

doi:10.1109/IESTEC46403.2019.00106

Early cardiac disease detection using neural networks

Hugo D. Calderon-Vilca, Kevin E.Chagua Callupe, Richard J.Inga Aliaga, Jair Barzola Cuba, Flor C. Marino-Cardenas

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

8 Citas (Scopus)

Resumen

Heart disease is one of the biggest problems in the world that will continue to be research. We have made an overview of the research related to heart disease. We verify that algorithms have been used for the classification of cardiac diseases: Apriori, decision tree, naive Bayesian. Neural network, SVM, ANN, KN and others. In this research, we have designed three architectures of neural networks to evaluate which of them adapts and predicts better the presence of heart diseases, we have determined that the architecture that best adapts is a neural network Backpropagation with quadratic error 0.01788 with a 99.26% accuracy. In addition, we have designed a web application tool to detect heart disease, this tool has been designed with the steps of software engineering.

Idioma original	Inglés
Título de la publicación alojada	Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019
Editorial	Institute of Electrical and Electronics Engineers Inc.
Páginas	562-567
Número de páginas	6
ISBN (versión digital)	9781728116914
DOI	https://doi.org/10.1109/IESTEC46403.2019.00106
Estado	Publicada - oct. 2019
Publicado de forma externa	Sí
Evento	7th International Engineering, Sciences and Technology Conference, IESTEC 2019 - Panama City, Panamá Duración: 9 oct. 2019 → 11 oct. 2019

Serie de la publicación

Nombre	Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019

Conferencia

Conferencia	7th International Engineering, Sciences and Technology Conference, IESTEC 2019
País/Territorio	Panamá
Ciudad	Panama City
Período	9/10/19 → 11/10/19

Nota bibliográfica

Publisher Copyright:
© 2019 IEEE.

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10.1109/IESTEC46403.2019.00106

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Calderon-Vilca, H. D., Callupe, K. E. C., Aliaga, R. J. I., Cuba, J. B., & Marino-Cardenas, F. C. (2019). Early cardiac disease detection using neural networks. En Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019 (pp. 562-567). Artículo 8943663 (Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IESTEC46403.2019.00106

Calderon-Vilca, Hugo D. ; Callupe, Kevin E.Chagua ; Aliaga, Richard J.Inga et al. / Early cardiac disease detection using neural networks. Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 562-567 (Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019).

@inproceedings{173863c747f84ddeae569853c9b5d6fa,

title = "Early cardiac disease detection using neural networks",

abstract = "Heart disease is one of the biggest problems in the world that will continue to be research. We have made an overview of the research related to heart disease. We verify that algorithms have been used for the classification of cardiac diseases: Apriori, decision tree, naive Bayesian. Neural network, SVM, ANN, KN and others. In this research, we have designed three architectures of neural networks to evaluate which of them adapts and predicts better the presence of heart diseases, we have determined that the architecture that best adapts is a neural network Backpropagation with quadratic error 0.01788 with a 99.26% accuracy. In addition, we have designed a web application tool to detect heart disease, this tool has been designed with the steps of software engineering.",

keywords = "Artificial intelligence, Backpropagation, Cardiac diseases, Early detection, Neural networks",

author = "Calderon-Vilca, {Hugo D.} and Callupe, {Kevin E.Chagua} and Aliaga, {Richard J.Inga} and Cuba, {Jair Barzola} and Marino-Cardenas, {Flor C.}",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 7th International Engineering, Sciences and Technology Conference, IESTEC 2019 ; Conference date: 09-10-2019 Through 11-10-2019",

year = "2019",

month = oct,

doi = "10.1109/IESTEC46403.2019.00106",

language = "Ingl{\'e}s",

series = "Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019",

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Calderon-Vilca, HD, Callupe, KEC, Aliaga, RJI, Cuba, JB & Marino-Cardenas, FC 2019, Early cardiac disease detection using neural networks. En Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019., 8943663, Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019, Institute of Electrical and Electronics Engineers Inc., pp. 562-567, 7th International Engineering, Sciences and Technology Conference, IESTEC 2019, Panama City, Panamá, 9/10/19. https://doi.org/10.1109/IESTEC46403.2019.00106

Early cardiac disease detection using neural networks. / Calderon-Vilca, Hugo D.; Callupe, Kevin E.Chagua; Aliaga, Richard J.Inga et al.
Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 562-567 8943663 (Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

TY - GEN

T1 - Early cardiac disease detection using neural networks

AU - Calderon-Vilca, Hugo D.

AU - Callupe, Kevin E.Chagua

AU - Aliaga, Richard J.Inga

AU - Cuba, Jair Barzola

AU - Marino-Cardenas, Flor C.

PY - 2019/10

Y1 - 2019/10

N2 - Heart disease is one of the biggest problems in the world that will continue to be research. We have made an overview of the research related to heart disease. We verify that algorithms have been used for the classification of cardiac diseases: Apriori, decision tree, naive Bayesian. Neural network, SVM, ANN, KN and others. In this research, we have designed three architectures of neural networks to evaluate which of them adapts and predicts better the presence of heart diseases, we have determined that the architecture that best adapts is a neural network Backpropagation with quadratic error 0.01788 with a 99.26% accuracy. In addition, we have designed a web application tool to detect heart disease, this tool has been designed with the steps of software engineering.

AB - Heart disease is one of the biggest problems in the world that will continue to be research. We have made an overview of the research related to heart disease. We verify that algorithms have been used for the classification of cardiac diseases: Apriori, decision tree, naive Bayesian. Neural network, SVM, ANN, KN and others. In this research, we have designed three architectures of neural networks to evaluate which of them adapts and predicts better the presence of heart diseases, we have determined that the architecture that best adapts is a neural network Backpropagation with quadratic error 0.01788 with a 99.26% accuracy. In addition, we have designed a web application tool to detect heart disease, this tool has been designed with the steps of software engineering.

KW - Artificial intelligence

KW - Backpropagation

KW - Cardiac diseases

KW - Early detection

KW - Neural networks

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BT - Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 7th International Engineering, Sciences and Technology Conference, IESTEC 2019

Y2 - 9 October 2019 through 11 October 2019

ER -

Calderon-Vilca HD, Callupe KEC, Aliaga RJI, Cuba JB, Marino-Cardenas FC. Early cardiac disease detection using neural networks. En Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 562-567. 8943663. (Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019). doi: 10.1109/IESTEC46403.2019.00106

Early cardiac disease detection using neural networks

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