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     Research Journal of Applied Sciences, Engineering and Technology

Research Article   |   OPEN ACCESS

A Novel Approach for the Diagnosis of Diabetes and Liver Cancer using ANFIS and Improved KNN

1C. Kalaiselvi and 2G.M. Nasira
1Department of Computer Applications, Tiruppur Kumaran College for Women, Karpagam University
2Department of Computer Applications, Chickanna Govt Arts College for Men, Tirupur, Tamilnadu, India
Research Journal of Applied Sciences, Engineering and Technology  2014  2:243-250
http://dx.doi.org/10.19026/rjaset.8.966  |  © The Author(s) 2014
Received: April ‎08, ‎2014  |  Accepted: April ‎28, ‎2014  |  Published: July 10, 2014
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Abstract

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.

Keywords:

Artificial neural network , K-nearest-neighbour , liver cancer , neuro fuzzy,

References