Fig. 5 | Scientific Reports

Fig. 5

From: A machine learning prediction model for Cardiac Amyloidosis using routine blood tests in patients with left ventricular hypertrophy

Fig. 5

Feature importance scores for the XGBoost algorithm using the routine blood test values. ANC, absolute neutrophils count; RBC, red blood cells; MCH, mean corpuscular he, moglobin; PDW, platelet distribution width; MCV, mean corpuscular volume; HGB, hemoglobin; RDW, erythrocyte distribution width; HCT, hematocrit; LYMPH#, lymphocytes count; MONO#, monocytes count; WBC, white blood cells; MCHC, mean corpuscular hemoglobin concentration; MPV, mean platelet volume; PLT, platelets; eGFR, estimated glomerular filtration rate; cTnI, cardiac troponin I; NT-proBNP, NT-proB-type natriuretic peptide; GGT, gamma glutamyl transferase; Glu, glucose; Chol, Cholesterol; ALT, alanine aminotransferase; K, potassium; Crea, creatinine; AST, aspartate aminotransferase; TG, triglyceride; UA, uric acid; ALb, albumin; TP, total protein; ALP, alkaline phosphatase; PCT, procalcitonin; LDH, lactate dehydrogenase; HDL-C, high density lipoprotein cholesterol; Na, sodium; DBIL, direct bilirubin; TBIL, total bilirubin; CL, Chlorine; Mg, magnesium; PT, prothrombin time; Fib, fibrinogen; APTT, activated partial thromboplastin time; FT3, free triiodothyronine; TSH, thyroid stimulating hormone; FT4, free thyroxine.

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