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Zhu XW, Yan J, He YL, Liu G, Li X. Application of deep learning based artificial intelligence technology in identification of colorectal polyps. Shijie Huaren Xiaohua Zazhi 2021; 29:1201-1206. [DOI: 10.11569/wcjd.v29.i20.1201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Colorectal cancer is a cancer type that is most suitable for screening since subjects at risk of this malignancy can clearly benefit from colonoscopy screening. In 2017, there were about 431951 new cases of colorectal cancer in China, with an increase of 203.5% in 28 years. Early detection and early removal of adenomatous polyps and other precancerous lesions during colonoscopy can prevent the occurrence of colorectal cancer. However, various factors lead to missed diagnosis of polyps during colonoscopy, which increases the risk of colorectal cancer. In recent years, with the rapid development of artificial intelligence technology in the medical field, colonoscopy assisted by artificial intelligence can increase the detection rate of polyps and improve the quality of colonoscopy. This paper mainly reviews the quality control, bowel preparation, diagnosis and classification of colorectal polyps, and the future opportunities and challenges faced by convolutional neural network based artificial intelligence technology in the field of colonoscopy, hoping to provide some reference for clinical work.
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Affiliation(s)
- Xing-Wang Zhu
- The First Clinical Medical College of Lanzhou University, Lanzhou 730000, Gansu Province, China
| | - Jun Yan
- The First Clinical Medical College of Lanzhou University, Lanzhou 730000, Gansu Province, China,Gansu Province Key Laboratory of Biological Therapy and Regenerative Medicine, Lanzhou 730000, Gansu Province, China,Cancer Prevention and Treatment Center of Lanzhou University School of Medicine, Lanzhou 730000, Gansu Province, China,Gansu Provincial Institute of Hepatobiliary and Pancreatic Surgery, Lanzhou 730000, Gansu Province, China,Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou 730000, Gansu Province, China
| | - Ying-Li He
- Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou 730000, Gansu Province, China
| | - Gang Liu
- Lanzhou University School of Information Science & Engineering, Lanzhou 730000, Gansu Province, China
| | - Xun Li
- The First Clinical Medical College of Lanzhou University, Lanzhou 730000, Gansu Province, China,Gansu Province Key Laboratory of Biological Therapy and Regenerative Medicine, Lanzhou 730000, Gansu Province, China,Cancer Prevention and Treatment Center of Lanzhou University School of Medicine, Lanzhou 730000, Gansu Province, China,Gansu Provincial Institute of Hepatobiliary and Pancreatic Surgery, Lanzhou 730000, Gansu Province, China,Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou 730000, Gansu Province, China
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