About this document
PaperID 1 by Tariqul Islam is a document available to read on EtoBox.
This study evaluates various deep learning architectures, particularly CNNs, for the automated classification of cholangiocarcinoma using medical imaging. DenseNet201 outperformed other models with a test accuracy of 93%, demonstrating efficiency in diagnosis with fewer parameters and reduced computational cost. The research aims to enhance early detection and improve diagnostic accuracy for cholangiocarcinoma, benefiting both patients and medical professionals.
- Author
- Tariqul Islam
- Language
- EN