Modelo Computacional para el análisis de historias clínicas de pacientes con Artritis Reumatoide aplicando bioinformática traslacional y minería de textos

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dc.contributor.advisorNiño Vasquez, Luis Fernando
dc.contributor.authorDel Risco Morales, Alexander
dc.contributor.educationalvalidatorQuintana Gerardo
dc.contributor.researchgrouplaboratorio de Investigación en Sistemas Inteligentes Lisispa
dc.date.accessioned2021-11-18T00:29:49Z
dc.date.available2021-11-18T00:29:49Z
dc.date.issued2021-11-16
dc.descriptionDocumento en pdf con imágenes y textospa
dc.description.abstractEste trabajo tiene como finalidad crear un modelo computacional que permita identificar el avance de la enfermedad de artritis reumatoide (AR) con base en el análisis de historias clínicas de pacientes diagnosticados con Artritis Reumatoide. Se plantea que mediante la minería de texto, se puede extraer la información que permita a los profesionales del área identificar datos relevantes para el proceso de diagnóstico de AR y de esta forma hacer un diagnóstico temprano de la misma, así también, se pretende aplicar el concepto de bioinformática traslacional, esto implica que la información de valor y que cumpla con los objetivos propuestos de esta investigación pueda ser transferida de forma efectiva a los pacientes que sufren esta enfermedad. Se ha desarrollado un modelo que aplica minería de textos, recuperación de la información, lingüística computacional, aprendizaje de máquina y otras áreas del conocimiento relacionadas, que permiten transformar y tratar los datos no estructurados para poder hacer el análisis correspondiente de las historias clínicas y así descubrir conocimiento implícito inmerso en las narrativas de las historias clínicas que ayude con el propósito de tener más y mejor información asociada a la artritis reumatoide y la evolución de los pacientes. (Texto tomado de la fuente)spa
dc.description.abstractThe purpose of this work is to create a computational model that allows to identify the progression of rheumatoid arthritis (RA) disease based on the analysis of medical records of patients diagnosed with rheumatoid arthritis. It is proposed that through text mining, information can be extracted which allows professionals in the area to identify relevant data for the RA diagnosis process and thus make an early diagnosis, therefore, it is also intended to apply the concept of translational bioinformatics, which implies that valuable information that meets the proposed objectives of this research can be effectively transferred to patients suffering from this disease. A model has been developed that applies text mining, information retrieval, computational linguistics, machine learning and other related areas of knowledge, which allow the transformation and processing of unstructured data in order to carry out the corresponding analysis of medical records and thus discover implicit knowledge immersed in the narratives of medical records that helps with the purpose of having more and better information associated with rheumatoid arthritis and the evolution of patients.eng
dc.description.curricularareaDepartamento ingeniería de Sistemas e Industrialspa
dc.description.degreelevelMaestríaspa
dc.description.degreenameMagíster en Bioinformáticaspa
dc.description.methodsInvestigación cualitativaspa
dc.description.researchareaBioinformáticaspa
dc.format.extent109 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.identifier.instnameUniversidad Nacional de Colombiaspa
dc.identifier.reponameRepositorio Institucional Universidad Nacional de Colombiaspa
dc.identifier.repourlhttps://repositorio.unal.edu.co/spa
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/80693
dc.language.isospaspa
dc.publisherUniversidad Nacional de Colombiaspa
dc.publisher.branchUniversidad Nacional de Colombia - Sede Bogotáspa
dc.publisher.departmentDepartamento de Ingeniería de Sistemas e Industrialspa
dc.publisher.facultyFacultad de Ingenieríaspa
dc.publisher.placeBogotá - Colombiaspa
dc.publisher.placeBogotá - Colombiaspa
dc.publisher.programBogotá - Ingeniería - Maestría en Bioinformáticaspa
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dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.licenseReconocimiento 4.0 Internacionalspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/spa
dc.subject.ddc000 - Ciencias de la computación, información y obras generales::003 - Sistemasspa
dc.subject.ddc000 - Ciencias de la computación, información y obras generales::005 - Programación, programas, datos de computaciónspa
dc.subject.ddc610 - Medicina y salud::616 - Enfermedadesspa
dc.subject.lembRheumatoid arthritis
dc.subject.proposalSnomedeng
dc.subject.proposalSnomedspa
dc.subject.proposalArtritis reumatoidespa
dc.subject.proposalRheumatoid arthritis
dc.subject.proposalBioinformática traslacionalspa
dc.subject.proposalTranslational bioinformaticseng
dc.subject.proposalMinería de textosspa
dc.subject.proposalText miningeng
dc.subject.proposalAprendizaje de máquinaspa
dc.subject.proposalMachine learningeng
dc.subject.proposalProcesamiento de lenguaje naturalspa
dc.subject.proposalNatural language processingeng
dc.titleModelo Computacional para el análisis de historias clínicas de pacientes con Artritis Reumatoide aplicando bioinformática traslacional y minería de textosspa
dc.title.translatedComputational Model for the analysis of clinical records of patients with Rheumatoid Arthritis applying translational bioinformatics and text miningeng
dc.typeTrabajo de grado - Maestríaspa
dc.type.coarhttp://purl.org/coar/resource_type/c_bdccspa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/masterThesisspa
dc.type.redcolhttp://purl.org/redcol/resource_type/TMspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
dcterms.audience.professionaldevelopmentEstudiantesspa
dcterms.audience.professionaldevelopmentInvestigadoresspa
dcterms.audience.professionaldevelopmentMaestrosspa
dcterms.audience.professionaldevelopmentPúblico generalspa
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2spa

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