Application of an artificial intelligence system for endoscopic diagnosis of superficial esophageal squamous cell carcinoma

Table 3 Characteristics of lesions that were inaccurately identified by the computer-assisted diagnosis system

Characteristics	Accurate identification (n = 186)	Inaccurate identification (n = 23)	P value
Lesion location, n (%)			1.000
Ce	2 (1.1)	0 (0)
Ut	13 (7.0)	2 (8.7)
Mt	152 (81.7)	20 (87.0)
Lt	19 (10.2)	1 (4.3)
Lesion size (cm), median (Q1, Q3)	2.0 (1.1-4.0)	3 (1.5-3.0)	0.476
Paris classification, n (%)			0.038
Type 0-IIb	95 (51.1)	17 (73.9)
Other non-flat types	91 (48.9)	6 (26.1)
Circumference, n (%)			0.591
< 1/4	107 (57.4)	10 (43.5)
1/4-1/2	54 (29.0)	9 (39.1)
1/2-3/4	16 (8.6)	2 (8.7)
> 3/4	9 (4.8)	2 (8.7)
Depth of invasion, n (%)			0.123
EP-LPM	144 (77.4)	21 (91.3)
MM and deeper	42 (22.6)	2 (8.7)

Ce: Cervical esophagus; Ut: Upper thoracic esophagus; Mt: Middle thoracic esophagus; Lt: Lower thoracic esophagus; Q1: Lower quantile; Q3: Upper quantile; EP-LPM: Epithelium or lamina propria; MM: Muscularis mucosa.