Please use this identifier to cite or link to this item: http://hdl.handle.net/10609/138908
Title: Análisis de los factores de riesgo de la enfermedad del Alzheimer y su detección temprana mediante machine learning
Author: Fernández Cobas, Hugo
Tutor: Olivares-Castiñeira, Ivette  
Others: Ventura, Carles  
Abstract: Nowadays, the development of new technologies such as machine learning (ML) has caused a flood of possibilities of use for solving problems. In our work, we will use this technology to carry out a study on Alzheimer's disease that includes: an analysis to know the different risk factors, the application of ML algorithms to prevent the disease from the study of these factors and the detection of patients from magnetic resonance imaging (MRI) using a convolutional neural network (CNN). With this, an improvement in the early detection and prevention of the disease is sought, which would allow us to apply the existing treatments to try to slow down its progress. This type of method may not be efficient on its own, because we obtained accuracies of approximately 60 %, but when combined with other types of tests (neuropsychological, fluid markers, etc.) they give good results.
Keywords: machine learning
Alzheimer
dementia
Document type: info:eu-repo/semantics/masterThesis
Issue Date: 24-Dec-2021
Publication license: http://creativecommons.org/licenses/by/3.0/es/  
Appears in Collections:Trabajos finales de carrera, trabajos de investigación, etc.

Files in This Item:
File Description SizeFormat 
hugofernandezcobas1221memoria.pdfMemoria del TFM2,64 MBAdobe PDFThumbnail
View/Open