Detection of Cardiovascular Diseases Using Predictive Models Based on Deep Learning Techniques: A Hybrid Neutrosophic AHP-TOPSIS Approach for Model Selection

Detection of Cardiovascular Diseases Using Predictive Models Based on Deep Learning Techniques: A Hybrid Neutrosophic AHP-TOPSIS Approach for Model Selection

In Ecuador and globally, cardiovascular diseases are the leading cause of mortality, accounting for a worrying 26.49% of deaths in 2019. An approach based on deep learning is applied to improve the capacity for early prediction and reduce its incidence. In this work, three different models were prop...

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Bibliographic Details
Main Authors: Julio Barzola-Monteses, Rosangela Caicedo-Quiroz, Franklin Parrales-Bravo, Cristhian Medina-Suarez, Wendy Yanez-Pazmino, David Zabala-Blanco, Maikel Y. Leyva-Vazquez
Format: Article
Language:English
Published: University of New Mexico 2024-12-01
Series:Neutrosophic Sets and Systems
Subjects:
heart disease
prediction
convolutional neural network
deep neural network
multilayer perceptron
neutrosophic ahp-topsis
Online Access:https://fs.unm.edu/NSS/17CardiovascularDiseases.pdf
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https://fs.unm.edu/NSS/17CardiovascularDiseases.pdf

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