Pronóstico mediante inteligencia artificial de los exámenes médico ocupacional del policlínico Juan Pablo de la Provincia de Nazca periodo 2019-2022
Fecha
2024
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Universidad Nacional San Luis Gonzaga
Resumen
La presente tesis de investigación tuvo como objetivo realizar el pronóstico de los
exámenes médico ocupacional de los pacientes del policlínico Juan Pablo de la ciudad
de Nazca periodo 2019-2022, El estudio del nivel predictivo, para un enfoque
cuantitativo, del tipo aplicado, utilizó los datos registrados en el periodo seleccionado
de los trabajadores de las empresas que se realizaron la evaluación para la aptitud o no
para el trabajo, la metodología utilizada CRISP-DM (Cross Industry Standard Process
for Data Mining) empleada para proyectos de dataming e inteligencia artificial, y como
herramienta se seleccionó el software Orange dataming por su aplicación gráfica para
el lenguaje python, que no requieren de conocimientos de programación. Los
resultados obtenidos para diversos algoritmos de predicción arrojan una precisión de
cerca del 80% para la regresión logística y las redes neuronales. La investigación
concluye que es muy importante realizar el pronóstico en este campo, que sirve como
ayuda a los profesionales de la salud en el análisis del diagnóstico la aptitud de los
trabajadores de las empresas que hacen uso del policlínico Juan pablo.
The present research thesis aimed to perform the prognosis of occupational medical examinations of patients of the Juan Pablo polyclinic of the city of Nazca period 2019-2022, The study of the predictive level, for a quantitative approach, of the applied type, used the data recorded in the selected period of the workers of the companies that were performed the evaluation for fitness or not for work, The methodology used was CRISP-DM (Cross Industry Standard Process for Data Mining) used for dataming and artificial intelligence projects, and the Orange dataming software was selected as a tool because of its graphical application for the Python language, which does not require programming knowledge. The results obtained for various prediction algorithms show an accuracy of about 80% for logistic regression and neural networks. The research concludes that it is very important to perform forecasting in this field, which serves as an aid to health professionals in the analysis of the diagnosis of the aptitude of the workers of the companies that make use of the Juan Pablo polyclinic.
The present research thesis aimed to perform the prognosis of occupational medical examinations of patients of the Juan Pablo polyclinic of the city of Nazca period 2019-2022, The study of the predictive level, for a quantitative approach, of the applied type, used the data recorded in the selected period of the workers of the companies that were performed the evaluation for fitness or not for work, The methodology used was CRISP-DM (Cross Industry Standard Process for Data Mining) used for dataming and artificial intelligence projects, and the Orange dataming software was selected as a tool because of its graphical application for the Python language, which does not require programming knowledge. The results obtained for various prediction algorithms show an accuracy of about 80% for logistic regression and neural networks. The research concludes that it is very important to perform forecasting in this field, which serves as an aid to health professionals in the analysis of the diagnosis of the aptitude of the workers of the companies that make use of the Juan Pablo polyclinic.
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Algoritmos, Inteligencia artificial, Exámenes médicos, Orange datamining, Artificial intelligence