Diagnosis and Classification of the Diabetes Using Machine Learning Algorithms

Author:

Theerthagiri Prasannavenkatesan,Ruby A. Usha,Vidya J.

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Computer Networks and Communications,Computer Graphics and Computer-Aided Design,Computational Theory and Mathematics,Artificial Intelligence,General Computer Science

Reference29 articles.

1. Lebovitz HE. Type 2 diabetes: an overview. Clin Chem. 1999;45(8):1339–45.

2. Mokdad AH, Ford ES, Bowman BA, Nelson DE, Engelgau MM, Vinicor F, Marks JS. Diabetes trends in the US: 1990–1998. Diabetes Care. 2000;23(9):1278–83.

3. Kalyani RR, Corriere MD, Donner TW, Quartuccio MW. Diabetes head to toe: everything you need to know about diagnosis, treatment, and living with diabetes. Baltimore: Johns Hopkins University Press; 2018.

4. Ali M, Tinna BA, Alexander RJ. A deep learning approach to adherence detection for type 2 diabetics. In: 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017.

5. Samrat KD, Ashraf H, Md. Mahbubur R. Implementation of a Web application to predict diabetes disease: an approach using machine-learning algorithm. In: 2018 21st International Conference of Computer and Information Technology (ICCIT), 2018, pp. 21–3.

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