Aprendizaje no supervisado: aplicación en epilepsia

Palabras clave: Epilepsia, Aprendizaje profundo, Aprendizaje automático, Auto codificación

Resumen

La epilepsia es uno de los trastornos neurológicos comunes caracterizado por convulsiones recurrentes. El objetivo principal de este artículo es dar a conocer el análisis de los resultados presentados en las gráficas de simulación de los datos de entrenamiento. Los datos fueron recolectados mediante el sistema 10-20. El sistema "10-20" es un método reconocido internacionalmente, este describe la ubicación de electrodos en la cabeza para una prueba de EEG. Se muestran las diferencias obtenidas entre las pruebas generadas con las anomalías de los datos de prueba a partir de los datos de entrenamiento. Finalmente, se interpretan los resultados y se discute sobre la eficacia del procedimiento.

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Cómo citar
Martínez-Toro, G. M., Rico-Bautista, D., Romero-Riaño, E., & Romero-Riaño, P. A. (2019). Aprendizaje no supervisado: aplicación en epilepsia. Revista Colombiana De Computación, 20(2), 20-27. https://doi.org/10.29375/25392115.3718

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Publicado
2019-12-01
Sección
Artículo de investigación científica y tecnológica