Integration of SVM with Artificial Fish Swarm Algorithm for Blood Tumour Prediction

Ms. N.R. Deepa, Dr. S. Gunasekaran, R. Elakiya, U. Haritha, N. Kaleeswari, P. Purnima

The growth of abnormal tissue is also called neoplasm which can be differentiated from the surrounding tissues by its structure. This tumour will affect the immune system which is a major leading cause of death around 13% worldwide. Blood diseases such as leukemia replaces the normal blood cells in the bone marrow and the blood. Effective modern drugs can be deployed for the blood diseases such as Chronic Lymphatic Leukemia(CLL). Data mining technique is used to categorize the blood test uniqueness(Hematology) and blood swelling to predict the disease in a early stage. Due to the increase in blood tumour diseases Support Vector Machine(SVM) is proposed for the classification of tumour and hematological data. Fish Swarm algorithm is found more efficient in optimizing the data with high accuracy.

https://doi.org/10.31871/IJNTR.5.3.32