Copyright
©The Author(s) 2021.
World J Gastroenterol. Aug 7, 2021; 27(29): 4802-4817
Published online Aug 7, 2021. doi: 10.3748/wjg.v27.i29.4802
Published online Aug 7, 2021. doi: 10.3748/wjg.v27.i29.4802
Ref. | Study design | Algorithm type | Dataset | Results |
Eickhoff et al[63] | Prospective, nonrandomized, unblinded feasibility study | CAD using NeoGuide Endoscopy System | 10 patients | 100% cecal intubation rate. Median time to cecum 20.5 min. 0 complications or adverse effects reported at discharge, 48 h, and 30 d |
Pullens et al[64] | Randomized control trial with crossover design | CAD using automated lumen centralization | 8 expert endoscopists and 10 endoscopy-naïve novices performing endoscopy on a validated colon model with 21 polyps | Novice |
Accuracy: 88.1% | ||||
Time to cecum: 8 min 56 s | ||||
Experts | ||||
Accuracy: 69% | ||||
Time to cecum: 13 min 1 s |
- Citation: Joseph J, LePage EM, Cheney CP, Pawa R. Artificial intelligence in colonoscopy. World J Gastroenterol 2021; 27(29): 4802-4817
- URL: https://www.wjgnet.com/1007-9327/full/v27/i29/4802.htm
- DOI: https://dx.doi.org/10.3748/wjg.v27.i29.4802