Clasificación de Arritmias Cardíacas mediante Redes Neuronales Convolucionales y Optimización por Enjambre de Partículas

Palabras clave: Redes Neuronales Convolucionales, Optimización por Enjambre de Partículas, Modelo Computacional, Clasificación de Arrimitas Cardíacas, Electrocardiogramas

Resumen

Una arritmia cardíaca es un latido irregular del corazón que se traduce en un impulso eléctrico anormal, y su tipo se define por el ritmo y duración. Su clasificación ha sido abordada en diferentes campos de la ciencia, destacando el uso de algoritmos de aprendizaje profundo. La presente investigación, utilizó un modelo híbrido entre Redes Neuronales Convolucionales y el algoritmo metaheurístico de Optimización por Enjambre de Partículas; para la clasificación de arritmias cardíacas. El metaheurístico se encargó de optimizar la arquitectura de capas de la red neuronal, a través de la minización de la pérdida durante el entrenamiento y prueba. Los datos se obtuvieron del MIT-BIH Arrhythmia dataset, donde se describen cinco categorías de arritmias. Los resultados logrados demostraron que el metaheurístico es un algoritmo confiable en la búsqueda de la mejor arquitectura de capas, logrando obtener una exactitud del 97%, lo que significa que el uso de técnicas metaheurísticas es una opción que se debe tomar en consideración a la hora de optimizar el rendimiento de las redes neuronales convolucionales.

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Publicado
2022-06-24
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Santander-Baños, F., Hernández-Romero, N., Barragán-Vite, I., Karelin, O., & Medina-Marín, J. (2022). Clasificación de Arritmias Cardíacas mediante Redes Neuronales Convolucionales y Optimización por Enjambre de Partículas. Pädi Boletín Científico De Ciencias Básicas E Ingenierías Del ICBI, 10(Especial2), 42-55. https://doi.org/10.29057/icbi.v10iEspecial2.8655
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