Decision-making model for early diagnosis of congestive heart failure using rough set and decision tree approaches

Article ID	Journal	Published Year	Pages	File Type
10355959	Journal of Biomedical Informatics	2012	10 Pages	PDF

Abstract

âº We have developed a decision-making model for CHF that uses RS and DT approaches. âº The model provides five critical factors and four decision rules associated with CHF. âº The four rules were found to be statistically significant (pÂ <Â 0.05). âº Pro BNP was critical in differentiating CHF patients from dyspnea patients.

Keywords

CK-MB ALT RBC creatine kinase MB fraction HCT WBC TcO2 LUC APTT MCH PLT MCHC MPV MCV AST Aspartate aminotransferase Alanine aminotransferase ALP Alkaline phosphatase Eosinophil Oxyhemoglobin saturation basophil BASO Base excess arterial blood gas analysis Mean corpuscular volume Maximum entropy principle BUN Occult blood Decision tree Total carbon dioxide activated partial thromboplastin time prothrombin time Sodium epithelial cell Platelet count EOs lactate dehydrogenase LDH Lymphocyte mean platelet volume mean corpuscular hemoglobin Rough set Decision-making model oxygen content Magnesium mono Monocyte Mean corpuscular hemoglobin concentration congestive heart failure Neut neutrophil blood urea nitrogen hematocrit Hemoglobin Specific gravity Potassium C-reactive protein CRP Creatine kinase Chloride white blood cell red blood cell