Advancements in Colorectal Cancer Predication and Classification using Deep Learning and Machine Learning Models

Abstract

The goal of this work is to provide a thorough assessment of the most recent research on AI-based machine learning and deep learning methods used in colorectal cancer modeling. A detailed synopsis and a list of the studies collected under each topic are then given. By focusing on the technical and medical viewpoints, we critically examine the prospects and difficulties in colorectal cancer prediction using ML and DL algorithms as we wrap up our work. Finally, we think that scientists who are thinking about using ML and DL techniques to diagnose colorectal cancer will find our study useful. This study provides a thorough analysis of the earlier advancements made by scientists in the prediction of colorectal cancer using both ML and DL algorithms.