Skip to main content
Fig. 3 | BMC Medical Informatics and Decision Making

Fig. 3

From: Machine learning to predict no reflow and in-hospital mortality in patients with ST-segment elevation myocardial infarction that underwent primary percutaneous coronary intervention

Fig. 3

Correlation analysis of the variables in the dataset for the prediction of in-hospital mortality, the dataset was not composed of many correlated variables, which indicated the model was simpler and more stable. ALB, albumin; Cr, creatinine; CK-MB, creatine kinase-MB; cTnI, cardiac troponin I; DM, diabetes mellitus; D-to-B, door-to-balloon; EF, ejection fraction; Fib, Fibrinogen; Glu, glucose; Hb, hemoglobin; Hbp, high blood pressure; HDL-C, high-density lipoprotein cholesterol; hs-CRP, high-sensitivity C-reactive protein; LDL-C, low-density lipoprotein cholesterol; PCI, percutaneous coronary intervention; SO-to-FMC, symptom-onset to-first medical contact; TC, total cholesterol; TG, triglyceride; TIMI, thrombolysis and thrombin inhibition in myocardial infarction; UA, uric acid; WBC, white blood cells

Back to article page