Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/187162
Title: Predicció resposta al tractament de càncer de mama
Author: Ramiro Bolívar, Joan
Director/Tutor: Díaz, Oliver
Keywords: Aprenentatge automàtic
Imatges per ressonància magnètica
Programari
Treballs de fi de grau
Càncer de mama
Xarxes neuronals convolucionals
Machine learning
Magnetic resonance imaging
Computer software
Breast cancer
Convolutional neural networks
Bachelor's theses
Issue Date: 24-Jan-2022
Abstract: [en] Breast cancer is the most widely diagnosed cancer, if it is detected in their early stages, it has a hight survival rate, 85 % if it is in the first stage. That’s why it is so important to act by early detection and choosing the best treatment to give to the patient. The aim of this study is to predict the complete pathological response of the patient, the prediction of their total care. To achieve it, a deep learning model will be developed, which by patient data and the magnetic ressonance image that is taken to him when the tumor is detected, will try to predict his pathological response. These data have been obtained thanks to the collaboration of the Hospital Parc Taulí in Sabadell, which provided it. The results obtained show potential although the model developed has not been as complex as it was intended from the beginning due to the lack of greater computing power. That’s why it would be a great idea to continue working in this field when having the necessary tools to be able to develop a model with greater complexity.
Note: Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2022, Director: Oliver Díaz
URI: http://hdl.handle.net/2445/187162
Appears in Collections:Programari - Treballs de l'alumnat
Treballs Finals de Grau (TFG) - Enginyeria Informàtica

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