An Intuitionistic Fuzzy Approach for Blood Data Analysis

The transfusion of quality blood and blood components is essential for the proper treatment of patients. Actions are regularly organized to encourage and popularize regular, anonymous and voluntary blood donation. It is of particular importance to improve the quality of the produced blood components. In this sense, it would be useful to be able to identify people who are potentially suitable as blood donors. In this way, it can be determined how many of the people in a given region are potential blood donors. The purpose of the present study is to investigate the relationships between blood parameters in order to determine whether the blood donor is suitable. The InterCriteria Analysis (ICA) approach was used as a research tool. The method uses two mathematical instruments: indexed matrices and intuitionistic fuzzy logic. Datasets containing information on age, gender, hemoglobin, red blood cell count, packed cell volume test, mean corpuscular volume, mean corpuscular hemoglobin, mean corpuscular hemoglobin concentration, red cell distribution width, total leucocyte count, platelet/mm3 (PLT/mm3) were examined. After applying the ICA method, intuitionistic fuzzy pairs were obtained, reflecting the degree of correlation between the analyzed parameters. Conclusions are drawn whether the blood donor is suitable, whether he can develop anemia, etc.