Comparative study on artificial intelligence systems for detecting early esophageal squamous cell carcinoma between narrow-band and white-light imaging

doi:10.3748/wjg.v27.i3.281

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Jan 21, 2021 (publication date) through Apr 25, 2024

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World Journal of Gastroenterology

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1007-9327

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

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World J Gastroenterol. Jan 21, 2021; 27(3): 281-293
Published online Jan 21, 2021. doi: 10.3748/wjg.v27.i3.281

Table 1 Patient and lesion characteristics in the validation image set

Patient characteristics, n = 112	Value
Median age, yr (range)	59 (19-86)
Sex, male/female	67/45
Lesion characteristics, n = 42
Median size, mm (range)	23 (9-42)
Location, Ce/Ut/Mt/Lt/Ae	0/3/24/15/0
Pathological diagnosis
LGIN/HGIN	6/18
Cancer, M/SM1	15/3

Ae: Abdominal esophagus; Ce: Cervical esophagus; HGIN: High-grade intraepithelial neoplasia; LGIN: Low-grade intraepithelial neoplasia; Lt: Lower thoracic esophagus; M: Mucosal; Mt: Middle thoracic esophagus; SM1: Submucosal; Ut: Upper thoracic esophagus.

Citation: Li B, Cai SL, Tan WM, Li JC, Yalikong A, Feng XS, Yu HH, Lu PX, Feng Z, Yao LQ, Zhou PH, Yan B, Zhong YS. Comparative study on artificial intelligence systems for detecting early esophageal squamous cell carcinoma between narrow-band and white-light imaging. World J Gastroenterol 2021; 27(3): 281-293
URL: https://www.wjgnet.com/1007-9327/full/v27/i3/281.htm
DOI: https://dx.doi.org/10.3748/wjg.v27.i3.281