CLASIFICACIÓN AUTOMÁTICA DE NIVEL DE ESTRÉS EN PERSONAL SANITARIO
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2023-10-03
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El nivel de estrés en el personal sanitario es un problema que
va en aumento, más aún, tras la pandemia. Desde el
sindicato de enfermería SATSE se ha realizado una encuesta
durante los años 2012, 2017 y 2021 para comprobar
precisamente algunos temas de salud mental por parte de los
profesionales de la salud. Este TFG propone el desarrollo
software para la implementación de diferentes modelos de
clasificación automática utilizando herramientas de
aprendizaje automático y técnicas de Procesamiento de
Lenguaje Natural (PLN). Concretamente se pretende
desarrollar un prototipo que a partir de los datos de
encuestas realizadas a profesionales clínicos sea capaz de
determinar si el profesional se encuentra o no estresado.
The level of stress in healthcare workers is a growing problem, even more so in the wake of the pandemic. even more so in the aftermath of the pandemic. From the nursing union SATSE has carried out a survey during during the years 2012, 2017 and 2021 to check precisely some mental health to check precisely some mental health issues on the part of health professionals. health professionals. This TFG proposes the development software for the implementation of different models of automatic classification models using machine learning tools and and Natural Language Processing (NLP) techniques. Natural Language Processing (NLP) techniques. Specifically, it is intended to to develop a prototype that, based on the data from surveys of surveys carried out on clinical professionals is able to determine whether or not determine whether the professional is stressed or not
The level of stress in healthcare workers is a growing problem, even more so in the wake of the pandemic. even more so in the aftermath of the pandemic. From the nursing union SATSE has carried out a survey during during the years 2012, 2017 and 2021 to check precisely some mental health to check precisely some mental health issues on the part of health professionals. health professionals. This TFG proposes the development software for the implementation of different models of automatic classification models using machine learning tools and and Natural Language Processing (NLP) techniques. Natural Language Processing (NLP) techniques. Specifically, it is intended to to develop a prototype that, based on the data from surveys of surveys carried out on clinical professionals is able to determine whether or not determine whether the professional is stressed or not
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Tratamiento inteligente de la Información