Rajesh

Rajesh, K. and Sangeetha, V. 2012 found that Medical professionals need a reliable prediction methodology to diagnose Diabetes. Data mining is applied to find useful patterns to help in the important tasks of medical diagnosis and treatment. In this paper they found that the data mining methods and techniques are explored to spot the appropriate method and techniques for efficient classification of diabetes dataset and in mining useful patterns. The result shows that a classification rate of 91% was obtained for C4.5 algorithm.6
Iyer, A. et al, 2015 observed that Diabetes has spread worldwide with a majority of them being women. This paper aims is finding solutions to diagnose the disease by analyzing the patterns found within the data through classification analysis by using Decision Tree and Naïve Bayes algorithms. They proposed a quicker and more efficient technique for diagnosing the disease, leading to timely treatment of the patients. The efficiency of the proposed model is showed by experimental result. Experimental results demonstrate the adequacy of the proposed model.7