Sanchita Paul

Work place: Birla Institute of Technology, Computer Science & Engineering, Mesra, Ranchi, India



Research Interests: Bioinformatics, Autonomic Computing, Computational Learning Theory


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:

Author Articles
GA_MLP NN: A Hybrid Intelligent System for Diabetes Disease Diagnosis

By Dilip Kumar Choubey Sanchita Paul

DOI:, 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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