Copyright: ©Author(s) 2026.
World J Gastroenterol. Aug 28, 2026; 32(32): 120382
Published online Aug 28, 2026. doi: 10.3748/wjg.120382
Published online Aug 28, 2026. doi: 10.3748/wjg.120382
Table 2 Confusion matrix of the gastric-tumour-infiltrating lymphocytes-convolutional neural network model on the test set, n (%)
| Actual label/predicted label | TIL | Non-TIL | Total | Recall (%) | Miss rate (%) | TNR (%) |
| TIL | 7632 (24.5) | 98 (0.3) | 7730 (24.8) | 98.7 | 1.3 | - |
| Non-TIL | 0 (0.0) | 23374 (75.2) | 23374 (75.2) | 100.0 | 0.0 | 100.0 |
| Total | 7632 (24.5) | 23472 (75.5) | 31104 (100) | - | - | - |
| Precision (%) | 100.0 | 99.6 | - | - | - | - |
| False discovery rate (%) | 0.0 | 0.4 | - | - | - | - |
- Citation: Fan Y, Wang SN, Jiang B, Li YY, Zhu CY, Liao XH, Zhang FS, Wang YK. Automatic recognition of tumour-infiltrating lymphocytes in pathological biopsy images of the gastric mucosa. World J Gastroenterol 2026; 32(32): 120382
- URL: https://www.wjgnet.com/1007-9327/full/v32/i32/120382.htm
- DOI: https://dx.doi.org/10.3748/wjg.120382