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Application of Machine Learning Algorithms to build a risk score for Pancreatic Cancer using high-throughput epidemiological risk factors

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dc.contributor.authorSobrino García, Víctor Manuel
dc.contributor.directorMartínez Tomás, Rafael
dc.date.accessioned2024-05-20T12:24:19Z
dc.date.available2024-05-20T12:24:19Z
dc.date.issued2020-03-01
dc.description.abstractCancer is one of the most challenging diseases that medical field is facing nowadays. Its incidence numbers are continuously increasing, and they are expected to keep on doing it for the next decades. Pancreatic Cancer is one of the most enigmatic among all the known cancer types. Even though the incidence numbers for PC are not so high as the ones for other diseases, its death ratio is astonishing. Life expectancy for people diagnosed with pancreatic cancer is less than six months. These numbers set up a difficult research environment where the characteristics of a risk population have not been, yet property identified, and where there is a lack of epidemiological information that makes further investigation in early detection very problematic. For the last decades, Artificial Intelligence has been demonstrating its benefits when applied to medical researches, since it can outperform human ability to identify trends and patterns inside huge datasets. In this work, I propose a novel and robust approach to identify the characteristic of a risk population in pancreatic cancer data that has been provided by surveys and researches performed in the whole Europe. This kind of data presents noise, bias and missing values that usually straiten the capabilities of the AI methods. The proposed system uses an ensemble of techniques that brings the ability to first recover the dataset and to later identify the most informative features that can be used to determine the characteristics of a risk population, to build a risk score for the epidemiological factors of Pancreatic Cancer.en
dc.description.versionversión final
dc.identifier.urihttps://hdl.handle.net/20.500.14468/14157
dc.language.isoen
dc.publisherUniversidad Nacional de Educación a Distancia (España). Escuela Técnica Superior de Ingeniería Informática. Departamento de Inteligencia Artificial.
dc.relation.centerE.T.S. de Ingeniería Informática
dc.relation.degreeMáster Universitario en I.A. Avanzada: Fundamentos, Métodos y Aplicaciones
dc.relation.departmentInteligencia Artificial
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
dc.subject.keywordsmachine learning
dc.subject.keywordspancreatic cancer
dc.subject.keywordsPanGen
dc.subject.keywordsrisk score
dc.subject.keywordsrisk population
dc.subject.keywordsimputation
dc.subject.keywordsfeatures selection
dc.subject.keywordsepidemiology
dc.titleApplication of Machine Learning Algorithms to build a risk score for Pancreatic Cancer using high-throughput epidemiological risk factorses
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dc.typemaster thesisen
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