Work place: Birla Institute of Technology, Computer Science & Engineering, Mesra, Ranchi, India
E-mail: Sanchita07@gmail.com
Website:
Research Interests: Bioinformatics, Autonomic Computing, Computational Learning Theory
Biography
Dr. Sanchita Paul, received her Ph.D degree and M.E. degree in Computer Science & Engineering from Birla Institute of Technology, Mesra, Ranchi, India and she has received B.E. degree in Computer Science & Engineering from Burdwan university, West Bengal, India. She has approximately 9 years of teaching and research experiences. She has 30 international publications. Her research areas include Machine learning, NLP, cloud computing, Bioinformatics, etc. Email: sanchita07@gmail.com
By Dilip Kumar Choubey Sanchita Paul
DOI: https://doi.org/10.5815/ijisa.2016.01.06, Pub. Date: 8 Jan. 2016
Diabetes is a condition in which the amount of sugar in the blood is higher than normal. Classification systems have been widely used in medical domain to explore patient’s data and extract a predictive model or set of rules. The prime objective of this research work is to facilitate a better diagnosis (classification) of diabetes disease. There are already several methodology which have been implemented on classification for the diabetes disease. The proposed methodology implemented work in 2 stages: (a) In the first stage Genetic Algorithm (GA) has been used as a feature selection on Pima Indian Diabetes Dataset. (b) In the second stage, Multilayer Perceptron Neural Network (MLP NN) has been used for the classification on the selected feature. GA is noted to reduce not only the cost and computation time of the diagnostic process, but the proposed approach also improved the accuracy of classification. The experimental results obtained classification accuracy (79.1304%) and ROC (0.842) show that GA and MLP NN can be successfully used for the diagnosing of diabetes disease.
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