Decision support system for anemia diagnosis based on fuzzy model

Anemia is considered one of the most common diseases that affect human body. In case prolonged existence, it can lead to development chronic due excessive load on vital organs. Effective treatments are available with early detection disease and largely depend its underlying cause. terms severity, anemia be divided into mild, moderate, severe according level hemoglobin. The morphological classification provides for division microcytic, normocytic, macrocytic depending average volume red blood cells. According hemoglobin, content hypochromic, normochromic hyperchromic. article explores scientific technical information fuzzy logic as well describes a decision support system diagnosis using inference model. During analysis existing literature, was found use naive Bayesian methods optimal solving problem determining anemia. But there possibility minor errors in measuring features, so necessary theory sets. Modulation implemented Mamdani algorithm. developed has two levels. first determines severity second responsible belonging classes: microcytic normocytic normochromic, macrocytic. software written Java basis own library implement computational algorithm by indicators hematological laboratory tests. application proposed architectural design saves time decision-making eliminates need additional manpower solve problems analytical management business processes monitoring