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dc.contributor.advisorSaltos Viteri, Harry Adolfo
dc.contributor.authorMacias Vera, Gilda Gisella
dc.date.accessioned2023-06-02T14:39:30Z
dc.date.available2023-06-02T14:39:30Z
dc.date.issued2023
dc.identifier.urihttp://dspace.utb.edu.ec/handle/49000/14191
dc.descriptionThe main problem in the hospitals of the city of Babahoyo is the lack of control and order in the records of patient examinations. This is due to the fact that a large amount of diverse data is handled, such as texts and images, which makes analysis difficult. The disorganization in the records causes incorrect diagnoses to be given, and inappropriate medicines to be prescribed, which can worsen the patients' condition. This represents a negative problem for patients, as they will not receive the proper treatment. As for the contribution of this technology, Machine Learning can help doctors avoid medical errors and improve patient safety. By analyzing data in an accurate and efficient way, Machine Learning algorithms can recognize medical errors and alert doctors so that they can take preventive measures. In conclusion, this tool has great potential to improve medical care by enabling doctors to analyze large data sets and make more informed decisions about the diagnosis and treatment of diseases. Finally, it should be noted that implementing Machine Learning to determine clinical pictures can have significant benefits, but it can also present significant challenges. It is necessary to carefully consider both the advantages and disadvantages of this technology before implementation and take appropriate measures to ensure data quality, patient privacy and safety, and the accuracy and transparency of the Machine Learning model used in healthcare.es_ES
dc.descriptionThe main problem in the hospitals of the city of Babahoyo is the lack of control and order in the records of patient examinations. This is due to the fact that a large amount of diverse data is handled, such as texts and images, which makes analysis difficult. The disorganization in the records causes incorrect diagnoses to be given, and inappropriate medicines to be prescribed, which can worsen the patients' condition. This represents a negative problem for patients, as they will not receive the proper treatment. As for the contribution of this technology, Machine Learning can help doctors avoid medical errors and improve patient safety. By analyzing data in an accurate and efficient way, Machine Learning algorithms can recognize medical errors and alert doctors so that they can take preventive measures. In conclusion, this tool has great potential to improve medical care by enabling doctors to analyze large data sets and make more informed decisions about the diagnosis and treatment of diseases. Finally, it should be noted that implementing Machine Learning to determine clinical pictures can have significant benefits, but it can also present significant challenges. It is necessary to carefully consider both the advantages and disadvantages of this technology before implementation and take appropriate measures to ensure data quality, patient privacy and safety, and the accuracy and transparency of the Machine Learning model used in healthcare.es_ES
dc.description.abstractLa principal problemática en los hospitales de la ciudad de Babahoyo es la falta de control y orden en los registros de los exámenes de los pacientes. Esto se debe a que se maneja una gran cantidad de datos de diversa índole, como textos e imágenes, lo que dificulta su análisis, La desorganización en los registros provoca que se entreguen diagnósticos incorrectos, y se prescriban medicinas inadecuadas, lo que puede empeorar la condición de los pacientes. Esto representa un problema negativo para los pacientes, ya que no recibirán el tratamiento adecuado. En cuanto al aporte de esta tecnología, el Machine Learning puede ayudar a los médicos a evitar errores médicos y mejorar la seguridad del paciente. Al analizar los datos de una manera precisa y eficiente, los algoritmos de Machine Learning pueden reconocer los errores médicos y alertar a los doctores para que puedan tomar medidas preventivas. En conclusión, esta herramienta tiene un gran potencial para mejorar la atención médica al permitir a los doctores analizar grandes conjuntos de datos y tomar decisiones más informadas sobre el diagnóstico y tratamiento de enfermedades. Finalmente cabe destacar que la implementación de la Machine Learning para determinar cuadros clínicos puede tener beneficios significativos, pero también puede presentar desafíos importantes. Es necesario considerar cuidadosamente tanto las ventajas como las desventajas de esta tecnología antes de su implementación y tomar medidas adecuadas para garantizar la calidad de los datos, la privacidad y seguridad de los pacientes, y la precisión y transparencia del modelo de Machine Learning utilizado en la atención médica.es_ES
dc.format.extent43 p.es_ES
dc.language.isoeses_ES
dc.publisherBabahoyo: UTB-FAFI. 2023es_ES
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Ecuador*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/ec/*
dc.subjectMachine Learninges_ES
dc.subjectMonitoreares_ES
dc.subjectAtención médicaes_ES
dc.titleEstudio relacionado con nuevas tecnologías de machine Learning para determinar cuadros clínicos.es_ES
dc.typebachelorThesises_ES


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