Reverter Comes, FerranLi, Shengnan2025-07-152025-07-152024https://hdl.handle.net/2445/222255Treballs Finals de Grau en Estadística UB-UPC, Facultat d'Economia i Empresa (UB) i Facultat de Matemàtiques i Estadística (UPC), Curs: 2023-2024, Tutor: Ferran Reverter ComesThis study explores using Convolutional Neural Networks (CNN) to predict microsatellite instability (MSI) and stability (MSS) from histology images in gastrointestinal cancer. A deep learning model was developed with Keras and TensorFlow in R, applying advanced techniques to histology images. The results show that deep CNN architectures effectively predict MSI and MSS, providing clinicians with a reliable tool to identify the microsatellite stability of tumor tissues.83 p.application/pdfengcc-by-nc-nd (c) Li, 2024http://creativecommons.org/licenses/by-nc-nd/3.0/es/Xarxes neuronals convolucionalsAprenentatge profundMedicinaEstadísticaTreballs de fi de grauConvolutional neural networksDeep learning (Machine learning)MedicineStatisticsBachelor's thesesinfo:eu-repo/semantics/bachelorThesisinfo:eu-repo/semantics/openAccess