The role of deep learning in diagnosing colorectal cancer
Dimitrios Bousis, Georgios‐Ioannis Verras, Konstantinos Bouchagier, Andreas Antzoulas, Ιoannis Panagiotopoulos, Anastasia Katinioti, Dimitrios Kehagias, Charalampos Kaplanis, Konstantinos Kotis, Christos‐Nikolaos Anagnostopoulos, Francesk Mulita
Abstract
Colon cancer is a major public health issue, affecting a growing number of individuals worldwide. Proper and early diagnosis of colon cancer is the necessary first step toward effective treatment and/or prevention of future disease relapse. Artificial intelligence and its subtypes, deep learning in particular, tend nowadays to have an expanding role in all fields of medicine, and diagnosing colon cancer is no exception. This report aims to summarize the entire application spectrum of deep learning in all diagnostic tests regarding colon cancer, from endoscopy and histologic examination to medical imaging and screening serologic tests.