Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/187162
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dc.contributor.advisorDíaz, Oliver-
dc.contributor.authorRamiro Bolívar, Joan-
dc.date.accessioned2022-06-29T07:25:25Z-
dc.date.available2022-06-29T07:25:25Z-
dc.date.issued2022-01-24-
dc.identifier.urihttp://hdl.handle.net/2445/187162-
dc.descriptionTreballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2022, Director: Oliver Díazca
dc.description.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.ca
dc.format.extent53 p.-
dc.format.mimetypeapplication/pdf-
dc.language.isocatca
dc.rightsmemòria: cc-nc-nd (c) Joan Ramiro Bolívar, 2022-
dc.rightscodi: GPL (c) Joan Ramiro Bolívar, 2022-
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/-
dc.rights.urihttp://www.gnu.org/licenses/gpl-3.0.ca.html*
dc.sourceTreballs Finals de Grau (TFG) - Enginyeria Informàtica-
dc.subject.classificationAprenentatge automàticca
dc.subject.classificationImatges per ressonància magnèticaca
dc.subject.classificationProgramarica
dc.subject.classificationTreballs de fi de grauca
dc.subject.classificationCàncer de mamaca
dc.subject.classificationXarxes neuronals convolucionalsca
dc.subject.otherMachine learningen
dc.subject.otherMagnetic resonance imagingen
dc.subject.otherComputer softwareen
dc.subject.otherBreast canceren
dc.subject.otherConvolutional neural networksen
dc.subject.otherBachelor's thesesen
dc.titlePredicció resposta al tractament de càncer de mamaca
dc.typeinfo:eu-repo/semantics/bachelorThesisca
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca
Appears in Collections:Programari - Treballs de l'alumnat
Treballs Finals de Grau (TFG) - Enginyeria Informàtica

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