APLICACIÓN DE REDES NEURONALES PARA LA CLASIFICACIÓN DE LOS NIVELES DE TENSIÓN ARTERIAL EN PACIENTES DE OCAÑA – NORTE DE SANTANDER
DOI:
https://doi.org/10.24054/rcta.v1i41.2415Keywords:
Modelo, Neurona, Nivel, Red, TensiónAbstract
El objetivo de esta investigación es modelar el comportamiento de la tensión arterial teniendo en cuenta dos factores como edad y género en pacientes de la ciudad de Ocaña – Norte de Santander. Para el desarrollo del proyecto se tienen en cuenta las etapas fundamentales del análisis de datos: adecuación de la base de datos, análisis exploratorio, comprobación de modelos de inteligencia artificial con redes neuronales clasificatorias; el carácter de la investigación es exploratoria con un enfoque cuantitativo y diseño no experimental. Se probaron varios modelos de redes neuronales con diferentes números de capas ocultas y cantidad de neuronas; se encontró que el modelo con mayor precisión era con dos capas ocultas de 100 neuronas cada una, lo que lograba una precisión de 87%. En conclusión, se pudo determinar un modelo de redes neuronales que, con las características de género y edad, más tensión diastólica y sistólica, puede clasificar al paciente en los niveles hipotensión, hipertensión, normal, optima, hipertensión sistólica o detectar alguna anomalía.
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