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©The Author(s) 2025.
World J Gastroenterol. Jun 7, 2025; 31(21): 107601
Published online Jun 7, 2025. doi: 10.3748/wjg.v31.i21.107601
Published online Jun 7, 2025. doi: 10.3748/wjg.v31.i21.107601
Table 4 Accuracy of different deep learning models in detecting lesions of normal mucosa, ulcers, erosions/erythema, and polyps
| Model | Overall accuracy (%) (95%CI) | Normal mucosa (%) (95%CI) | Ulcers (%) (95%CI) | Erosions/erythema (%) (95%CI) | Polyps (%) (95%CI) |
| DenseNet121 | 90.6 (89.2-92.0) | 98.6 (96.0-100) | 83.3 (75.6-91.1) | 81.9 (74.2-89.6) | 100 (100-100) |
| VGG16 | 88.3 (87.9-88.8) | 92.2 (89.7-94.6) | 91.6 (89.9-93.3) | 72.1 (63.6-80.6) | 75.0 (66.8-83.2) |
| ResNet50 | 90.5 (89.9-91.1) | 98.1 (96.8-99.4) | 87.0 (82.3-91.7) | 77.3 (72.4-82.2) | 100 (100-100) |
| ViT | 88.1 (86.7-89.6) | 93.2 (88.5-97.9) | 87.4 (77.6-97.3) | 73.0 (61.3-84.8) | 87.9 (76.3-99.5) |
- Citation: Huang YH, Lin Q, Jin XY, Chou CY, Wei JJ, Xing J, Guo HM, Liu ZF, Lu Y. Classification of pediatric video capsule endoscopy images for small bowel abnormalities using deep learning models. World J Gastroenterol 2025; 31(21): 107601
- URL: https://www.wjgnet.com/1007-9327/full/v31/i21/107601.htm
- DOI: https://dx.doi.org/10.3748/wjg.v31.i21.107601