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Table 2 Description of the data set

From: Application of machine learning missing data imputation techniques in clinical decision making: taking the discharge assessment of patients with spontaneous supratentorial intracerebral hemorrhage as an example

Variables

Categories

Discharge situation

Success (n = 1207)

Failure (n = 261)

Age

 < 55

249 (20.6%)

37 (14.2%)

 

55–64

265 (22.0%)

51 (19.5%)

 

65–74

391 (32.4%)

86 (33.0%)

 

75–84

246 (20.4%)

60 (23.0%)

 

 > 84

56 (4.6%)

27 (10.3%)

Gender

Male

688 (57.0%)

163 (62.5%)

 

Female

519 (43.0%)

98 (37.5%)

More than two times of in-hospital

No

1194 (98.9%)

251 (96.2%)

 

Yes

13 (1.1%)

10 (3.8%)

Deep coma

No

1190 (98.6%)

130 (49.8%)

 

Yes

17 (1.4%)

131 (50.2%)

Diagnostic location

Deep

1081 (89.6%)

220 (84.3%)

 

Superficial

126 (10.4%)

41 (15.7%)

Supratentorial hemorrhage volume

 < 30 ml

1032 (85.5%)

128 (49.0%)

 

 ≥ 30 ml

175 (14.5%)

133 (51.0%)

Operation

No

1045 (86.6%)

203 (77.8%)

 

Yes

162 (13.4%)

58 (22.2%)

Co-infection

No

802 (66.4%)

138 (52.9%)

 

Yes

405 (33.6%)

123 (47.1%)