Copyright
©The Author(s) 2020.
World J Gastroenterol. Oct 21, 2020; 26(39): 5911-5918
Published online Oct 21, 2020. doi: 10.3748/wjg.v26.i39.5911
Published online Oct 21, 2020. doi: 10.3748/wjg.v26.i39.5911
Table 1 The overall adenoma detection rate of these studies was significantly higher while aided by computer aided detection systems
| Ref. | Study type | CADe system | ARM | ADR |
| Repici et al[25], 2020 | Multicenter RCT | GI Genius | WL | 40, 40% |
| CADe | 54, 80% | |||
| Wang et al[26], 2019 | Monocenter RCT | Endoscreener | WL | 20% |
| CADe | 29% | |||
| Wang et al[27], 2020 | Monocenter RCT | Endoscreener | WL | 28% |
| CADe | 34, 10% | |||
| Gong et al[28], 2020 | Monocenter RCT | ENDOANGEL | WL | 8, 20% |
| CADe | 16, 70% | |||
| Liu et al[29], 2020 | Monocenter RCT | HenanTongyu | WL | 24% |
| CADe | 39, 20% |
- Citation: Sinagra E, Badalamenti M, Maida M, Spadaccini M, Maselli R, Rossi F, Conoscenti G, Raimondo D, Pallio S, Repici A, Anderloni A. Use of artificial intelligence in improving adenoma detection rate during colonoscopy: Might both endoscopists and pathologists be further helped. World J Gastroenterol 2020; 26(39): 5911-5918
- URL: https://www.wjgnet.com/1007-9327/full/v26/i39/5911.htm
- DOI: https://dx.doi.org/10.3748/wjg.v26.i39.5911