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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 |
Files in This Item:
File | Description | Size | Format | |
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codi.zip | Codi font | 310.32 kB | zip | View/Open |
tfg_ramiro_bolivar_joan.pdf | Memòria | 3.61 MB | Adobe PDF | View/Open |
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