Transfer Learning Based Model for Colon Cancer Prediction Using VGG16

Abstract

Colon cancer, or a colorectal cancer, is a malignant neoplasm that originates in the colon. It is one of the most prevalent forms of cancer globally, with significant impacts on morbidity and mortality rates. The essential task is to detect it and detect it at an initial phase for curing the patient precisely. The artificial intelligence plays important roles in the colon cancer prediction. The authors proposed various models on colon cancer prediction using ML and DL. The existing approaches are unable to achieve good accuracy for the colon cancer prediction. This research work suggests a transfer learning based framework for the colon cancer prediction. This framework is planned on the basis of VGG16 and CNN in colon cancer prediction. The proposed framework is implemented in python and results is analysed concerning accuracy, precision, recall. © 2023 IEEE.