Copyright: ©Author(s) 2026.
World J Gastroenterol. Jun 7, 2026; 32(21): 117299
Published online Jun 7, 2026. doi: 10.3748/wjg.v32.i21.117299
Published online Jun 7, 2026. doi: 10.3748/wjg.v32.i21.117299
Table 4 The impact of artificial intelligence assistance on the detection rate of high-risk gastric lesions in anesthetized patients of propensity score matching groups, n (%)
| Lesion types | Non-AI group (n = 6540) | AI group (n = 6656) | OR (95%CI) | P value |
| LGIN | 19 (0.29) | 42 (0.63) | 2.18 (1.27-3.75) | 0.005 |
| HGIN | 5 (0.08) | 14 (0.21) | 2.76 (0.99-7.65) | 0.052 |
| EGC | 10 (0.15) | 22 (0.33) | 2.17 (1.03-4.58) | 0.043 |
| HrGLs | 29 (0.44) | 60 (0.90) | 2.04 (1.31-3.19) | 0.002 |
- Citation: Ying JX, Yan SY, Fu XY, Zhou YJ, Zhou JJ, Yang Y, Zhou XB, Wang ZZ, Li SW, Fang LN, Mao XL. Artificial intelligence-assisted endoscopists improve the detection rate of high-risk gastric lesions: A propensity score-matched retrospective study. World J Gastroenterol 2026; 32(21): 117299
- URL: https://www.wjgnet.com/1007-9327/full/v32/i21/117299.htm
- DOI: https://dx.doi.org/10.3748/wjg.v32.i21.117299