Application of Random Forest Survival Models to Increase Generalizability of Decision Trees: A Case Study in Acute Myocardial Infarction

Table 1

Demographic characteristics of patients.

Predictor variables	Levels	Number (percent%)
Sex	Male/female	423 (69.7)/184 (30.3)
Hypertension disease	Yes/no	245 (40.4)/362 (59.6)
Hyperlipidemia	Yes/no	135 (22.2)/472 (77.8)
History of ischemic heart disease	Yes/no	184 (30.3)/423 (69.7)
Diabetes	Yes/no	150 (24.7)/457 (75.3)
Smoking status	Yes/no	216 (35.6)/391 (64.4)
Family history of AMI disease	Yes/no	63 (10.4)/544 (89.6)
Q wave status	Yes/no	159 (26.2)/448 (73.8)
Streptokinase treatment	Yes/no	278 (45.8)/329 (54.2)
Intervention	Angioplasty	32 (5.3)
	Pacemaker surgery	36 (5.9)
	Bypass surgery	45 (7.4)
	Drug therapy	494 (81.4)