Comparison between multiple logistic regression and machine learning methods in prediction of abnormal thallium scans in type 2 diabetes

Table 1 Participant demographics

Variables	mean ± SD	N
Age	67.38 ± 9.69	556
Body mass index	26.16 ± 3.9	556
Duration of diabetes	13.69 ± 7.94	556
Systolic blood pressure	131.14 ± 15.42	493
Diastolic blood pressure	73.32 ± 10.15	493
Hemoglobin	12.92 ± 1.68	444
Triglyceride	153.74 ± 45.85	539
Glycated hemoglobin	7.79 ± 1.36	538
High density lipoprotein cholesterol	122.65 ± 74.34	535
Low density lipoprotein cholesterol	49.65 ± 14.75	498
Alanine aminotransferase	23.87 ± 13.94	537
Creatinine	1.16 ± 1	536
Microalbumin creatinine ratio	194.18 ± 733.73	526
Homeostasis assessment-insulin resistance	0.63 ± 0.34	366
Homeostasis assessment-insulin secretion	1.71 ± 0.37	366