Detection of Thrombocytopenia, Anemia and Leukocytosis by Using Ensemble Learning

Abstract

Blood disorders are conditions that impact the blood’s ability to function correctly. There is a range of different symptoms depending on the type. There are several different types of blood disorders such as Leukemia, chronic myelocytic leukemia, lymphoma, myelofibrosis, polycythemia, Thrombocytopenia, anemia and Leukocytosis. Some resolve completely with therapy, or do not cause symptoms and do not affect overall lifespan Some are chronic and lifelong but do not affect how long you live. Other blood disorders, like sickle cell disease and blood cancers, can be fatal. Thereneeds to capture of hidden information in the medical data for detecting diseases in the early stage. In this study, we apply the Ensemble Learning technique for classification. We compared our result with other classification methods. The results show that Ensemble Learning methods can predict the Tumor of blood disease better than the other classifiers.