Medical aid system for Alzheimer's diagnosis using machine learning
dc.contributor.advisorTFE | Paternain Dallo, Daniel | |
dc.contributor.advisorTFE | Galar Idoate, Mikel | |
dc.contributor.affiliation | Escuela Técnica Superior de Ingeniería Industrial, Informática y de Telecomunicación | es_ES |
dc.contributor.affiliation | Industria, Informatika eta Telekomunikazio Ingeniaritzako Goi Mailako Eskola Teknikoa | eu |
dc.contributor.author | Urtasun Urra, Jon | |
dc.date.accessioned | 2021-02-12T14:43:35Z | |
dc.date.available | 2021-02-12T14:43:35Z | |
dc.date.issued | 2021 | |
dc.date.updated | 2021-02-11T10:52:48Z | |
dc.description.abstract | Artificial Intelligence (AI), and precisely Machine Learning (ML), has been proved to be a considerably useful method in a wide variety of fields. One of the fields that has improved more is the computer vision. Computers can now apply ML techniques in order to solve tasks, such as image classification, which were inconceivable in the past. This led into a huge impact on the medicine field, which has increasingly ameliorated over the recent years. The purpose of this project is to prove whether ML techniques are able to successfully diagnose Alzheimer’s disease or not. | en |
dc.description.degree | Graduado o Graduada en Ingeniería Informática por la Universidad Pública de Navarra | es_ES |
dc.description.degree | Informatika Ingeniaritzako Graduatua Nafarroako Unibertsitate Publikoan | eu |
dc.format.mimetype | application/pdf | en |
dc.identifier.uri | https://academica-e.unavarra.es/handle/2454/39189 | |
dc.language.iso | eng | en |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | |
dc.subject | Alzheimer | en |
dc.subject | Machine learning | en |
dc.subject | MRI | en |
dc.subject | Dataset | en |
dc.subject | Convolutional neural network | en |
dc.subject | SVM | en |
dc.title | Medical aid system for Alzheimer's diagnosis using machine learning | en |
dc.type | info:eu-repo/semantics/bachelorThesis | |
dspace.entity.type | Publication | |
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