Copyright
©The Author(s) 2020.
World J Gastroenterol. Oct 14, 2020; 26(38): 5784-5796
Published online Oct 14, 2020. doi: 10.3748/wjg.v26.i38.5784
Published online Oct 14, 2020. doi: 10.3748/wjg.v26.i38.5784
I-scan optical enhancement | NBI | BLI | |
Ref. | Everson et al[11] | Sharma et al[12] | Subramaniam et al[13] |
Features assessed | Mucosal pit pattern, vessels | Mucosal pit pattern, vessels | Colour, mucosal pit patterns, vessels |
Accuracy | Experts = 84%, non-experts = 76% | 85% | Experts = 95.2%, non-experts = 88.3% |
Sensitivity | Experts = 77%, non-experts = 81% | 80% | Experts = 96%, non-experts = 95.7% |
Specificity | Experts = 92%, non-experts = 70% | 88% | Experts = 94.4%, non-experts = 80.8% |
- Citation: Hussein M, González-Bueno Puyal J, Mountney P, Lovat LB, Haidry R. Role of artificial intelligence in the diagnosis of oesophageal neoplasia: 2020 an endoscopic odyssey. World J Gastroenterol 2020; 26(38): 5784-5796
- URL: https://www.wjgnet.com/1007-9327/full/v26/i38/5784.htm
- DOI: https://dx.doi.org/10.3748/wjg.v26.i38.5784