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https://hdl.handle.net/2445/222255| Title: | Classification of medical images with convolutional networks |
| Author: | Li, Shengnan |
| Director/Tutor: | Reverter Comes, Ferran |
| Keywords: | Xarxes neuronals convolucionals Aprenentatge profund Medicina Estadística Treballs de fi de grau Convolutional neural networks Deep learning (Machine learning) Medicine Statistics Bachelor's theses |
| Issue Date: | 2024 |
| Abstract: | This 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. |
| Note: | Treballs 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 Comes |
| URI: | https://hdl.handle.net/2445/222255 |
| Appears in Collections: | Treballs Finals de Grau (TFG) - Estadística UB-UPC |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| TFG-EST_Li.pdf | 7.56 MB | Adobe PDF | View/Open |
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