Automatic recognition of tumour-infiltrating lymphocytes in pathological biopsy images of the gastric mucosa

Table 3 Tumour-infiltrating lymphocyte recognition performance of the gastric-tumour-infiltrating lymphocytes-convolutional neural network for different gastric mucosal lesions (%)

Lesion type	Accuracy (95%CI)	Specificity (95%CI)	Sensitivity (95%CI)
Chronic atrophic gastritis	99.1 (98.5-99.7)	99.5 (99.1-99.9)	98.8 (98.0-99.6)
Intestinal metaplasia	98.6 (97.8-99.4)	99.2 (98.6-99.8)	97.9 (96.8-99.0)
High-grade intraepithelial neoplasia	99.3 (98.7-99.9)	99.7 (99.3-100.0)	99.0 (98.2-99.8)
Early gastric cancer	99.5 (99.0-100.0)	100.0 (99.8-100.0)	99.1 (98.4-99.8)

P < 0.05. This table is based on the statistics of 96 samples in the test set, with 24 cases for each lesion type. The accuracy of the intestinal metaplasia group was the lowest, mainly because of the slight misjudgment caused by the similar morphology between the goblet cells and scattered tumour-infiltrating lymphocytes. CI: Confidence interval.