Abstract
Diabetes is a menacing disease, which can cause death without any cautions. In this paper we introduce a way to assist people by raising an alert for precautions. It is a prediction system for the diabetes disease, which will predict whether to be a candidate and at what age. The datasets are for Egyptian diabetes patients, 2/3 will be used for training and 1/3 will be used for testing. This system is based on the machine learning concept, by using decision tree technique. This paper introduces a new idea in prediction and differs from previous papers, which focused on classification prediction to answer a yes or no question only. This contribution was new in the prediction system, by adding a regression technique with a randomization code to predict the age. The results were promising, the system predicts diabetes incidents at what age, with accuracy 84 %.
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© 2016 Springer International Publishing Switzerland
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Orabi, K.M., Kamal, Y.M., Rabah, T.M. (2016). Early Predictive System for Diabetes Mellitus Disease. In: Perner, P. (eds) Advances in Data Mining. Applications and Theoretical Aspects. ICDM 2016. Lecture Notes in Computer Science(), vol 9728. Springer, Cham. https://doi.org/10.1007/978-3-319-41561-1_31
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DOI: https://doi.org/10.1007/978-3-319-41561-1_31
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