Published online Nov 6, 2021. doi: 10.12998/wjcc.v9.i31.9376
Peer-review started: June 15, 2021
First decision: July 15, 2021
Revised: July 26, 2021
Accepted: August 13, 2021
Article in press: August 13, 2021
Published online: November 6, 2021
Processing time: 136 Days and 0.4 Hours
Colorectal cancer has the second highest incidence of malignant tumors and is the fourth leading cause of cancer deaths in China. Early diagnosis and treatment of colorectal cancer will lead to an improvement in the 5-year survival rate, which will reduce medical costs. The current diagnostic methods for early colorectal cancer include excreta, blood, endoscopy, and computer-aided endoscopy. In this paper, research on image analysis and prediction of colorectal cancer lesions based on deep learning is reviewed with the goal of providing a reference for the early diagnosis of colorectal cancer lesions by combining computer technology, 3D modeling, 5G remote technology, endoscopic robot technology, and surgical navigation technology. The findings will supplement the research and provide insights to improve the cure rate and reduce the mortality of colorectal cancer.
Core Tip: The development of computer technology has promoted the progress of medical treatment. Artificial intelligence (AI) has been gradually applied in the medical field and achieved good results. The detection of colorectal lesions in the conventional gastrointestinal endoscopy is difficult, the diagnosis time is long, and there is often the problem of missed diagnosis and misdiagnosis. AI is a good aid for doctors. In this review, we summarize the application of AI in the detection of colorectal lesions in recent years, in order to provide reference for the follow-up development and research.