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©The Author(s) 2022.
World J Gastroenterol. Oct 7, 2022; 28(37): 5483-5493
Published online Oct 7, 2022. doi: 10.3748/wjg.v28.i37.5483
Published online Oct 7, 2022. doi: 10.3748/wjg.v28.i37.5483
Table 1 Characteristics of subjects and lesions involved in the testing dataset
Characteristics | Values |
Cancerous cases (n = 209) | |
Age (yr), mean ± SD | 62.0 ± 7.2 |
Sex, Male/Female | 158/51 |
Lesion location, Ce/Ut/Mt/Lt/Ae | 2/21/172/14/0 |
Lesion size (cm), median (Q1, Q3) | 2.0 (1.2-4.0) |
Paris classification, 0-I/IIa/IIb/IIc/IIa+IIc/III | 6/43/112/26/20/2 |
Circumference, < 1/4, 1/4-1/2, 1/2-3/4, > 3/4 | 117/63/18/11 |
Depth of invasion, EP-LPM/MM-SM1/SM2 | 165/38/6 |
Non-Cancerous cases (n = 114) | |
Age (yr), mean ± SD | 63.2 ± 5.3 |
Sex, male/female | 65/49 |
Endoscopic diagnosis, GERD/submucosal lesion/normal | 23/5/86 |
- Citation: Meng QQ, Gao Y, Lin H, Wang TJ, Zhang YR, Feng J, Li ZS, Xin L, Wang LW. Application of an artificial intelligence system for endoscopic diagnosis of superficial esophageal squamous cell carcinoma. World J Gastroenterol 2022; 28(37): 5483-5493
- URL: https://www.wjgnet.com/1007-9327/full/v28/i37/5483.htm
- DOI: https://dx.doi.org/10.3748/wjg.v28.i37.5483