A Comparative study using Machine Learning and Data Mining Approach for Leukemia

Leukemia is a type of blood cancer which impacts the white blood cells and damages the bone marrow. Usually the Complete Blood Count (CBC) and bone marrow get affected. It can be a fatal disease if not identified at the earliest level. In exercise, manual microscopic assessment of the sample slide is used for analysis of Leukemia. But manual diagnostic strategies are time taking, less in accuracy, and often have errors due to diverse human elements like pressure, fatigue, and so on. To retrieve the possible faults, errors and assisting the doctors, clustering and classification techniques are required. So, the authors have done rigorous analysis and study of many research articles based on Leukemia diseases interesting majorly in the classification algorithm. The prime objective of this review article is to analyse and compare techniques on Leukemia disease.