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 5 Influence of artificial intelligence assistance on detection rate of high-risk gastric lesions in different parts of stomach in propensity score matching groups, n (%)
| Location of lesion | AI group (n = 7764) | Non-AI group (n = 7764) | OR (95%CI) | P value |
| Cardia | 11 (0.14) | 6 (0.08) | 1.84 (0.68-4.96) | 0.232 |
| Gastric fundus | 3 (0.04) | 1 (0.01) | 3.00 (0.31-28.85) | 0.341 |
| Gastric body | 11 (0.14) | 5 (0.06) | 2.20 (0.77-6.34) | 0.144 |
| Gastric angle | 11 (0.14) | 3 (0.04) | 3.67 (1.02-13.16) | 0.046 |
| Gastric antrum | 35 (0.45) | 23 (0.30) | 1.52 (0.90-2.58) | 0.117 |
| Gastric pylorus | 3 (0.04) | 3 (0.04) | 1.00 (0.20-4.96) | 1.000 |
- 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