Abstract
The aim of study is comparative analysis of two algorithms co-adaptive neuro fuzzy inference system classifiers for better efficiency with adaptive neuro fuzzy inference system for brain tumor detection. Materials and Methods: The data set used for this experiment is taken from Kaggle open access dataset. A total of 20 brain magnetic resonance images are used forco-adaptive neuro fuzzy inference system (Group 1) it is compared with adaptive neuro fuzzy inference system (Group 2). To measure the accuracy 80% of the images are used for training, 10% for testing and 10% for validation. Threshold 0.05 and g-power is 80. The performance analysis is done to validate the better methodology in the SPSS Tool. Result: The initial research using adaptive neuro fuzzy inference system(ANFIS) in detection of brain tumor disease has achieved accuracy of 93% and the proposed system has attained accuracy of 96%. Conclusion: It is concluded that the detection of innovative brain tumor in this view, the diagnosis of brain tumor disease using co-adaptive neuro fuzzy inference system (CANFIS) appears to be with better results compared to adaptive neuro fuzzy inference system (ANFIS).
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