Método de autoaprendizaje basado en machine learning aplicado a la dieta de un individuo con colitis ulcerativa. Caso de estudio: paciente Juan Pablo Aguirre Martínez

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dc.contributor.advisorEspinosa Bedoya, Albeiro
dc.contributor.authorAguirre Martínez, Juan Pablo
dc.contributor.cvlacJuan Pablo Aguirre Martínezspa
dc.contributor.researchgatehttps://www.researchgate.net/profile/Juan-Pablo-Aguirre-Martinezspa
dc.contributor.researchgroupCalidad de Softwarespa
dc.date.accessioned2025-06-10T14:11:36Z
dc.date.available2025-06-10T14:11:36Z
dc.date.issued2025-06-09
dc.descriptionIlustraciones, gráficos, tablasspa
dc.description.abstractLa Colitis Ulcerativa (CU), es una Enfermedad Inflamatoria Intestinal (EII), crónica que afecta a aproximadamente 1 de cada 1000 personas en el mundo. Esta condición autoinmune provoca inflamación y úlceras en el colon, desencadenando síntomas como diarrea, sangrado, dolor y fatiga, reduciendo significativamente la calidad de vida. La severidad puede oscilar entre leve a grave, e incluso puede ser potencialmente mortal. Si bien no existe una cura, la nutrición personalizada es clave en el manejo de los síntomas. Este trabajo propone un método basado en técnicas de autoaprendizaje y Machine Learning para ajustar la alimentación de individuos con CU, tomando como caso de estudio al paciente Juan Pablo Aguirre Martínez. La justificación de este radica en la falta de literatura previa sobre la aplicación de sistemas de Machine Learning a la dieta de personas con CU. La metodología incluye la construcción de un conjunto de datos, la revisión y evaluación de técnicas de Machine Learning. Precisamente, se consideró la capacidad del modelo para procesar datos temporales y aprender de manera continua, lo que llevó a la elección del modelo LSTM. Se espera que el método propuesto contribuya al desarrollo de una herramienta innovadora que mejore la calidad de vida de personas con CU y fomente la exploración de nuevas soluciones en el ámbito de la medicina. (Tomado de la fuente)spa
dc.description.abstractUlcerative Colitis (UC) is a chronic Inflammatory Bowel Disease (IBD) affecting approximately 1 in 1000 people worldwide. This autoimmune condition causes inflammation and ulcers in the colon, triggering symptoms such as diarrhea, bleeding, pain, and fatigue, significantly reducing the patient’s quality of life. The severity of the disease can range from mild to critical, and in extreme cases, it may even become life-threatening. Although there is no cure, personalized nutrition plays a key role in symptom management. This study proposes a method based on self-learning techniques and Machine Learning to adjust the diet of individuals with UC, using patient Juan Pablo Aguirre Martínez as a case study. The justification for this research lies in the lack of prior literature on the application of Machine Learning systems to the diet of individuals with UC. The methodology includes the construction of a dataset, as well as the review and evaluation of Machine Learning techniques. Specifically, the model's ability to process temporal data and continuously learn was considered, leading to the selection of the LSTM model. The proposed method aims to develop an innovative tool that enhances the quality of life for individuals with UC while fostering the exploration of novel solutions in medicine.eng
dc.description.curricularareaIngeniería De Sistemas E Informática.Sede Medellínspa
dc.description.degreelevelMaestríaspa
dc.description.degreenameMagister en Ingeniería – Analíticaspa
dc.description.researchareaAprendizaje Automáticospa
dc.format.extent72 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/88216
dc.language.isospaspa
dc.publisherUniversidad Nacional de Colombiaspa
dc.publisher.branchUniversidad Nacional de Colombia - Sede Medellínspa
dc.publisher.facultyFacultad de Minasspa
dc.publisher.placeMedellín, Colombiaspa
dc.publisher.programMedellín - Minas - Maestría en Ingeniería - Analíticaspa
dc.relation.indexedLaReferenciaspa
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dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.licenseReconocimiento 4.0 Internacionalspa
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/spa
dc.subject.ddc000 - Ciencias de la computación, información y obras generales::006 - Métodos especiales de computaciónspa
dc.subject.ddc610 - Medicina y salud::616 - Enfermedadesspa
dc.subject.ddc600 - Tecnología (Ciencias aplicadas)::607 - Educación, investigación, temas relacionadosspa
dc.subject.ddc620 - Ingeniería y operaciones afines::629 - Otras ramas de la ingenieríaspa
dc.subject.lembColitis ulcerativa - Estudio de casos
dc.subject.lembEnfermedades del colon - Estudio de casos
dc.subject.lembAprendizaje automático (Inteligencia artificial)
dc.subject.lembHábitos alimenticios - Estudio de casos
dc.subject.lembProcesamiento de datos
dc.subject.proposalColitis Ulcerativaspa
dc.subject.proposalMétodo de autoaprendizajespa
dc.subject.proposalAprendizaje no supervisadospa
dc.subject.proposalAprendizaje supervisadospa
dc.subject.proposalAlimentaciónspa
dc.subject.proposalNutriciónspa
dc.subject.proposalUlcerative Colitiseng
dc.subject.proposalMachine Learningeng
dc.subject.proposalSelf-Learning Methodeng
dc.subject.proposalUnsupervised Learningeng
dc.subject.proposalSupervised Learningeng
dc.subject.proposalDieteng
dc.subject.proposalNutritioneng
dc.titleMétodo de autoaprendizaje basado en machine learning aplicado a la dieta de un individuo con colitis ulcerativa. Caso de estudio: paciente Juan Pablo Aguirre Martínezspa
dc.title.translatedSelf-learning method based on machine learning applied to the diet of an individual with ulcerative colitis. Case study: patient Juan Pablo Aguirre Martínezeng
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.contentOtherspa
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
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2spa
oaire.awardtitleMétodo de autoaprendizaje basado en Machine Learning aplicado a la dieta de un individuo con Colitis Ulcerativa.spa

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