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Abstract
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Article Information:
A Novel Approach for the Diagnosis of Diabetes and Liver Cancer using ANFIS and Improved KNN
C. Kalaiselvi and G.M. Nasira
Corresponding Author: C. Kalaiselvi
Submitted: April 08, 2014
Accepted: April 28, 2014
Published: July 10, 2014 |
Abstract:
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The multi-factorial, chronicle, severe diseases are cancer and diabetes. As a result of abnormal level of glucose in body leads to heart attack, kidney disease, renal failure and cancer. Many studies have been proved that several types of cancer are possible in diabetes patients having a high blood sugar. Many approaches are proposed in the past to diagnose both cancer and diabetes. Even though the existing approaches are efficient one, the classification accuracy is poor. An Enhanced approach is proposed to achieve a higher efficiency and lower complexity. Adaptive neuro fuzzy inference system is used to classify the dataset with the help of adaptive group based KNN. The Pima Indian diabetes dataset are used as input dataset and classified based on the attribute information. The experimental result shows the classification accuracy is better than the existing approaches such FLANN, ANN with FUZZYKNN.
Key words: Artificial neural network, K-nearest-neighbour, liver cancer, neuro fuzzy, , ,
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Cite this Reference:
C. Kalaiselvi and G.M. Nasira, . A Novel Approach for the Diagnosis of Diabetes and Liver Cancer using ANFIS and Improved KNN. Research Journal of Applied Sciences, Engineering and Technology, (2): 243-250.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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