A novel framework for esophageal cancer grading: combining CT imaging, radiomics, reproducibility, and deep learning insights

A novel framework for esophageal cancer grading: combining CT imaging, radiomics, reproducibility, and deep learning insights

Abstract Objective This study aims to create a reliable framework for grading esophageal cancer. The framework combines feature extraction, deep learning with attention mechanisms, and radiomics to ensure accuracy, interpretability, and practical use in tumor analysis. Materials and methods This ret...

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Bibliographic Details
Main Authors: Muna Alsallal, Hanan Hassan Ahmed, Radhwan Abdul Kareem, Anupam Yadav, Subbulakshmi Ganesan, Aman Shankhyan, Sofia Gupta, Kamal Kant Joshi, Hayder Naji Sameer, Ahmed Yaseen, Zainab H. Athab, Mohaned Adil, Bagher Farhood
Format: Article
Language:English
Published: BMC 2025-05-01
Series:BMC Gastroenterology
Subjects:
Esophageal cancer grading
CT imaging
Radiomics
Deep learning
Reproducibility
Online Access:https://doi.org/10.1186/s12876-025-03952-6
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https://doi.org/10.1186/s12876-025-03952-6

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