Detection of type of thalassemia disease in patients: A fuzzy logic approach

In this paper, we have determined the severity of Thalassemia disease in a patient with the help of their Red Blood Cell (RBC) indices components such as Mean Corpuscular Hemoglobin (MCH) and Mean corpuscular volume (MCV). Also level of blood (Hemoglobin) is considered. We use a fuzzy application, the Mamdani Fuzzy Inference System (FIS) to generate a model for Thalassemia diagnosis. Obtained model is applied on set of data such that 15 results are similar and 3 are marginally off. It shows that the accuracy of the proposed system is 83.3%. Sensitivity analysis is carried out the result of which shows that the developed Thalassemia diagnosis model is more stable. From the viewpoint of an end-user, the results of this work can facilitate laboratory work by reducing the time and cost.