About this document
Federated Learning for Cancer Classification by jobaerislam16 is a document available to read on EtoBox.
This study presents a collaborative federated learning framework aimed at improving the classification of lung and colon cancers through histopathological image analysis while ensuring patient data privacy. The proposed model achieved high classification accuracies of 99.867% for lung cancer and 100% for colon cancer, demonstrating its effectiveness compared to existing methods. The framework facilitates collaboration among healthcare organizations by allowing them to train local models without sharing sens
- Author
- jobaerislam16
- Language
- EN