From: Machine learning prediction of mortality in Acute Myocardial Infarction
Variable | Experiment 1 | Experiment 2 | Experiment 3 |
---|---|---|---|
Age | X | X | X |
Sex | X | X | X |
Type of AMI | X | X | X |
Comorbidities | X | X | X |
Laboratory findings (n) | 25 | 33 | 33 |
Laboratory findings | Albumin, Erythrocyte Distribution Range (RDW-CV), Calcium, Creatinine, Creatine kinase (CK), Eosinophils, Erythrocytes, Glucose, Hematocrit, Haemoglobin, Mean globular haemoglobin (HGM), International Normalised ratio (INR), Lactate Dehydrogenase (LDH), Lymphocytes, Neutrophils, Platelets, Potassium, C-reactive protein, Sodium, Activated Partial Thromboplastin Time (APTT), Prothrombin time, Glutamic-oxalacetic transaminase, Glutamic-pyruvic transaminase (SGPT), Troponin I, Urea | ||
 | Chlorine, Phosphokinase MM fraction (CK-MB), Arterial bicarbonate concentration (HCO3a), Mean corpuscular haemoglobin concentration (MCHC), Magnesium, Mean Platelet Volume (MPV), Blood oxygen (pO2), Blood oxygen saturation (sO2) | ||
N. º of comorbidities |  | X | X |
Surgical Intervention | Â | X | X |
Body mass index | Â | Â | X |
Symptoms | Â | Â | X |
ACS Time | Â | Â | X |
Heart Rate | Â | Â | X |
N.º of Segments with Injury |  |  | X |