ABSTRACT
Colorectal cancer (CRC) is a prominent source of illness and death worldwide. Detection and precise diagnosis of CRC at an early stage can significantly enhance patient outcomes. Artificial intelligence (AI) has yielded promising results in the detection and classifications of CRC. The application of machine learning (ML) algorithms, deep learning (DL), and computerassisted diagnosis systems are only a few of the most current advances in the use of AI techniques for CRC detection and diagnosis that we discuss in this study. In the article, we also compared and evaluated the CRC detection work of various researchers using various performance parameters such as accuracy and loss. We also examine the types and epidemiology of CRC, which aids in the diagnosis of the numerous CRC cancer types. AI has the possible to substantially enhance the detection and diagnosis of cancer, leading to improved patient health and lower healthcare costs.
