Una revisión de las implementaciones de sistemas para la identificación de tendencias de la diabetes

Palabras clave: diabetes mellitus, identificación de tendencias, software preventivo, métodos de construcción, regresión logística, redes neuronales artificiales

Resumen

La diabetes mellitus es una enfermedad crónica que aparece cuando el páncreas no secreta suficiente insulina o cuando el organismo no utiliza apropiadamente la insulina que produce. Dado que la insulina es una hormona que regula la concentración de glucosa en la sangre, uno de los efectos más comunes de la diabetes no controlada es la hiperglucemia, que con el tiempo daña gravemente muchos órganos y sistemas del cuerpo. Por ello, es importante el desarrollo de software predictivo para el diagnóstico y posterior tratamiento de esta enfermedad, en particular para la diabetes tipo 1 y 2, que concentran la mayoría de los casos. El presente trabajo realiza una revisión sistemática de literatura a fin de determinar los métodos
y la problemática en la construcción de sistemas de identificación de tendencias orientados a la diabetes. Los resultados muestran 16 métodos diferentes de construcción utilizados en estos sistemas, de los cuales los más eficientes son la regresión logística y las redes neuronales artificiales.

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Publicado
2022-12-23
Cómo citar
Benites Loja, R. I., & Coral Ygnacio, M. A. (2022). Una revisión de las implementaciones de sistemas para la identificación de tendencias de la diabetes. Interfases, 16(016), 231-251. https://doi.org/10.26439/interfases2022.n016.5957
Sección
Artículos de revisión