Addressing Label Noise in Colorectal Cancer Classification Using Cross-Entropy Loss and pLOF Methods With Stacking-Ensemble Technique

Addressing Label Noise in Colorectal Cancer Classification Using Cross-Entropy Loss and pLOF Methods With Stacking-Ensemble Technique

Colorectal cancer is a significant global health issue, ranking as the third most common cancer and the second leading cause of cancer-related deaths worldwide. Early diagnosis of this disease is of utmost importance to increase the survival rate and enhance the healthcare system. Many machine learn...

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Bibliographic Details
Main Authors: Ishrat Zahan Tani, Kah Ong Michael Goh, Md Nazmul Islam, Md Tarek Aziz, S. M. Hasan Mahmud, Dip Nandi
Format: Article
Language:English
Published: Wiley 2025-01-01
Series:Applied Computational Intelligence and Soft Computing
Online Access:http://dx.doi.org/10.1155/acis/6552580
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