A recommender system for detection of leukemia based on cooperative game

Cancer is a term used for diseases in which abnormal cells divide without control and invade other tissues. Cancer types can be grouped into broader categories including leukemia, carcinoma, sarcoma, lymphoma and myeloma, central nervous system cancers among them, Leukemia is a form of serious cancers that starts in blood tissue such as the bone marrow where all the blood is made. It is one of the leading causes of death in the world. So, the importance of diagnostic techniques is manifested. Application of these techniques would be able to decrease the mortality rate from leukemia. In this paper, an automatic system for classifying leukemia based on game theory is presented. The aim of this research is to apply game theory in order to classify leukemia into eight classes. In other words, cooperative game is used for classification according to different weights assigned to the markers. Through out this paper, we work on real data (304 samples) taken from different types of leukemia that have been collected at Iran Blood Transfusion Organization (IBTO). The modeling system can be used to model and classify a population according to their contributions. In the other words, it applies equally to other groups of data. The results show that the highest classification accuracy (98.44%) is obtained for the proposed model. So, it is hoped that game theory can be directly used for classification in the other cases.