Table 2 Data summaries for the training, internal validation and internal validation test groups.

From: Artificial intelligence-aided method to detect uterine fibroids in ultrasound images: a retrospective study

Variables

Training dataset (n = 1416)

Internal validation dataset (n = 336)

External validation dataset (n = 268)

P value

Diameter of uterine fibroids (cm)

   

0.53

< 4 cm

180 (12.7%)

37 (11.0%)

30 (11.2%)

 

≥ 4 cm and < 8 cm

1038 (73.3%)

247 (73.5%)

191 (71.3%)

 

≥ 8 cm

198 (14.0%)

52 (15.5%)

47 (17.5%)

 

Number of fibroids

   

0.26

Single

680 (48.0%)

147 (43.8%)

134 (50%)

 

Multiple (\(\ge\) 2)

736 (52.0%)

189 (56.2%)

134 (50%)

 

Type of fibroids

   

0.17

Sub serous fibroids

86 (6.1%)

13 (3.9%)

10 (3.7%)

 

Intramural fibroids

1214 (85.7%)

303 (90.2%)

237 (88.4%)

 

Submucosal fibroids

116 (8.2%)

20 (5.9%)

21 (7.8%)

 

Location of fibroids

   

0.005

Cervix

11 (0.8%)

4 (1.2%)

5 (1.9%)

 

Ante theca

377 (26.6%)

83 (24.7%)

58 (21.6%)

 

Posterior

420 (29.7%)

134 (39.9%)

101 (37.7%)

 

Fundus

136 (9.6%)

27 (8.0%)

25 (9.3%)

 

The left side

187 (13.2%)

31 (9.2%)

24 (9.0%)

 

The right side

169 (11.9%)

37 (11.0%)

34 (12.7%)

 

Uterine cavity

116 (8.2%)

20 (6.0%)

21 (7.8%)

 

Type of ultrasound

   

0.04

Transvaginal

1042 (73.6%)

267 (79.5%)

209 (78.0%)

 

Abdominal

374 (26.4%)

69 (20.5%)

59 (22.0%)

 
  1. Except where indicated, the data are numbers of ultrasound images with percentages in parentheses.