Diabetes Detection and Prediction Using Machine Learning/IoT: A Survey-Reference-Cited by-同舟云学术

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Diabetes Detection and Prediction Using Machine Learning/IoT: A Survey

Published:2018-12-12 Issue: Volume: Page:471-479
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
language:
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Author:

Sharma Neha,Singh Ashima

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-13-3140-4_42

Reference24 articles.

1. Xu, W., Zhang, J., Zhang, Q., Wei, X.: Risk prediction of type II diabetes based on random forest model. In: Advances in Electrical, Electronics, Information, Communication and Bio-Informatics (AEEICB). (2017). https://doi.org/10.1109/aeeicb.2017.7972337

2. Gandhi, K.K., Prajapati, N.B.: Diabetes prediction using feature selection and classification. Int. J. Adv. Eng. Res. Develop. (2014). https://doi.org/10.21090/ijaerd.0105110

3. Panwar, M., Acharyya, A., Shafik, R.A., Biswas, D.: K-nearest neighbor based methodology for accurate diagnosis of diabetes mellitus. In: Embedded Computing and System Design (ISED), pp. 132–136. IEEE (2016). https://doi.org/10.15417/1881

4. Sowjanya, K., Singhal, A., Choudhary, C.: MobDBTest: a machine learning based system for predicting diabetes risk using mobile devices. In: Advance Computing Conference (IACC), pp. 397–402. IEEE (2015). https://doi.org/10.1109/iadcc.2015.7154738

5. Heydari, M., Teimouri, M., Heshmati, Z., Alavinia, S.M.: Comparison of various classification algorithms in the diagnosis of type 2 diabetes in Iran. Int. J. Diabetes Develop. Countries, 167–173. (2016). https://doi.org/10.15417/1881

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