Abstract
Diabetes is a common disease throughout the world. It is generally in sleep mode, whenever the patient suffers from any disease, diabetes boosts them. It is a common factor of cardiac problem. Authors try to detect it using multilayer perceptron neural network in this paper. The case study is of Indian ladies with pregnancy suffer from diabetes. Data considered from PIMA database from UCI repository and are used. Eight attributes are taken as features for each subject. It has been verified for 768 patients. The common MLP classifier is utilized for attributes and the experiment is learned with R studio platform. The performance found to be better as compared to earlier methods and verified in MATLAB platform as well.
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Mohapatra, S.K., Swain, J.K., Mohanty, M.N. (2019). Detection of Diabetes Using Multilayer Perceptron. In: Bhaskar, M., Dash, S., Das, S., Panigrahi, B. (eds) International Conference on Intelligent Computing and Applications. Advances in Intelligent Systems and Computing, vol 846. Springer, Singapore. https://doi.org/10.1007/978-981-13-2182-5_11
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DOI: https://doi.org/10.1007/978-981-13-2182-5_11
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