Copyright: ©Author(s) 2026.
World J Gastroenterol. Jul 21, 2026; 32(27): 119276
Published online Jul 21, 2026. doi: 10.3748/wjg.119276
Published online Jul 21, 2026. doi: 10.3748/wjg.119276
Table 2 Model generalization performance tests
| Test content | Recall % (95%CI) | Precision % (95%CI) | Accuracy % (95%CI) |
| Ileocecal recognition generalization | |||
| The first time | 96.15 (96.05, 96.25) | 99.34 (99.13, 99.55) | 97.76 (97.27, 98.25) |
| The second time | 96.79 (96.34, 97.24) | 98.69 (98.33, 99.05) | 97.75 (97.52, 97.98) |
| The third time | 96.15 (95.89, 96.41) | 99.34 (98.93, 99.75) | 97.76 (97.11, 98.41) |
| Mucosa touch recognition generalization | |||
| The first time | 98.72 (98.39, 99.05) | 100.00 (100.00, 100.00) | 99.36 (99.03, 99.69) |
| The second time | 100.00 (100.00, 100.00) | 100.00 (100.00, 100.00) | 100.00 (100.00, 100.00) |
| The third time | 98.72 (98.43, 99.01) | 100.00 (100.00, 100.00) | 99.36 (99.00, 99.72) |
- Citation: Chen W, Wu M, Wang HY, Wu HB, Li J, Sun YH, Huang F, Gao M, Zhong ZH, Wu YM, Chen L. Artificial intelligence-based mucosa touch rate: A novel real-time quality control indicator for colonoscopy. World J Gastroenterol 2026; 32(27): 119276
- URL: https://www.wjgnet.com/1007-9327/full/v32/i27/119276.htm
- DOI: https://dx.doi.org/10.3748/wjg.119276