An Artificial Intelligence Outlook for Colorectal Cancer Screening

TL;DR

This paper reviews how artificial intelligence can enhance colorectal cancer screening by integrating non-invasive risk estimation and blood protein markers into decision support systems, aiming to improve early detection and reduce mortality.

Contribution

It proposes a framework combining AI with blood-based biomarkers and risk factors for more effective colorectal cancer screening.

Findings

AI-enabled risk estimation improves screening accuracy

Blood-derived protein markers show potential for early detection

Framework supports clinical decision-making

Abstract

Colorectal cancer is the third most common tumor in men and the second in women, accounting for 10% of all tumors worldwide. It ranks second in cancer-related deaths with 9.4%, following lung cancer. The decrease in mortality rate documented over the last 20 years has shown signs of slowing down since 2017, necessitating concentrated actions on specific measures that have exhibited considerable potential. As such, the technical foundation and research evidence for blood-derived protein markers have been set, pending comparative validation, clinical implementation and integration into an artificial intelligence enabled decision support framework that also considers knowledge on risk factors. The current paper aspires to constitute the driving force for creating change in colorectal cancer screening by reviewing existing medical practices through accessible and non-invasive risk estimation, employing a straightforward artificial intelligence outlook.