Copyright: ©Author(s) 2026.
World J Gastroenterol. Oct 7, 2026; 32(37): 119857
Published online Oct 7, 2026. doi: 10.3748/wjg.119857
Published online Oct 7, 2026. doi: 10.3748/wjg.119857
Table 1 Baseline characteristics of phase 3 participants, n (%)
| Characteristic | ChatGPT5 (n = 20) | DeepSeek (n = 20) | Overall (n = 40) | P value | |
| Age (years), mean ± SD | 40.4 ± 9.8 | 40.8 ± 10.1 | 40.6 ± 9.8 | 0.899 | |
| Sex | 1.000 | ||||
| Male | 9 (45.0) | 9 (45.0) | 18 (45.0) | ||
| Female | 11 (55.0) | 11 (55.0) | 22 (55.0) | ||
| Education level | 0.805 | ||||
| Junior high school or below | 1 (5.0) | 2 (10.0) | 3 (7.5) | ||
| Senior high school/vocational high school | 8 (40.0) | 9 (45.0) | 17 (42.5) | ||
| College or above | 11 (55.0) | 9 (45.0) | 20 (50.0) |
- Citation: Sun SP, Niu DY, Yuan MK, Liu L, Li Y, Min H. Evaluating large language models in Helicobacter pylori-related question answering: From knowledge tests to patient queries. World J Gastroenterol 2026; 32(37): 119857
- URL: https://www.wjgnet.com/1007-9327/full/v32/i37/119857.htm
- DOI: https://dx.doi.org/10.3748/wjg.119857