EFFECTIVE ANALYSIS OF BRAIN TUMOR USING HYBRID DATA MINING TECHNIQUES

BVKIRANMA YEE, Dr.T.V. RAJINIKANTH, DR.S.NAGINI NAGINI

Abstract


In the recent era there has been a rapid growth in the availability of medical databases and medical imagery in the past few years, and the uncertainty involved in the effective prediction of diseases from these databases made the research community to take up the challenges in this domain.The Central Nervous System of mankind being is mainly composed of Spinal Cord, Brain and Neurons. Largest part of brain is Cerebrum. The human brain throws good number of challenges to the research community. The Brain Tumour or the Intra Cranial Neoplasm is formed due to the irregular growth of cells in the brain. This sort of irregular growth of cells in brain damages frontal, temporal and parietal lobes thereby results in abnormal behaviour. Machine learning algorithms provide computers with the ability to learn without being explicitly programmed. The clinical brain data set was analysed effectively using machine learning algorithms and made conclusions on the results. In this paper we applied Hybrid Data Mining methods which in turn consists of Clustering, Classification andAssociation techniques and further analysed the results using some statistical techniques.

Keywords


Brain Tumor,Machine Learning Algorithms, Clinical brain data set, Hybrid Data mining Techniques, Statistical

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DOI: https://doi.org/10.26483/ijarcs.v8i7.4237

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