Publication: ur72. Aplicación web para la predicción del retorno de pacientes al servicio de urgencias de un hospital en el plazo de 72 horas
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2021
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Abstract
Uno de los factores que determina la calidad de los servicios de urgencias de cualquier hospital, es la tasa de retorno de los pacientes a dichos servicios en un corto plazo de tiempo(24, 48 o 72 horas).
En este trabajo se pretende crear una herramienta que ayude a los profesionales de los centros hospitalarios en su labor. Para ello se ha creado una aplicación web, donde una de las principales funciones será pronosticar el porcentaje que tiene un paciente de regresar al hospital en un periodo de 72 horas, si es dado de alta.
Como punto de partida disponemos de los informes de ingresos de pacientes del “Hospital San Juan de Dios del Aljarafe”, Sevilla, de los años 2015, 2016, 2017 y 2018. Con estos datos alimentaremos una red neural que se encargará de realizar la predicción.
One of the factors that determines the quality of emergency services in any hospital is the rate return of patients to these services in a short period of time (24, 48 or 72 hours). The target of this work, is to create a tool that helps hospital professionals in their work. For it, this web application has been created, one of the main functions will be to forecast the percentage that a patient has to return to the hospital in a period of 72 hours, if he is discharged. As a starting point, we have the patient admissions reports from the “Hospital San Juan de Dios del Aljarafe”, Sevilla, of the years 2015, 2016, 2017 and 2018. With this data we will feed a neural network that will be in charge of making the prediction.
One of the factors that determines the quality of emergency services in any hospital is the rate return of patients to these services in a short period of time (24, 48 or 72 hours). The target of this work, is to create a tool that helps hospital professionals in their work. For it, this web application has been created, one of the main functions will be to forecast the percentage that a patient has to return to the hospital in a period of 72 hours, if he is discharged. As a starting point, we have the patient admissions reports from the “Hospital San Juan de Dios del Aljarafe”, Sevilla, of the years 2015, 2016, 2017 and 2018. With this data we will feed a neural network that will be in charge of making the prediction.
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Trabajo de Fin de Grado en Ingeniería de Computadores, Facultad de Informática UCM, Departamento de Sistemas Informáticos y Computación, Curso 2020/2021