IoT based prediction of chronic kidney disease
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Publisher
AIP Publishing
Link
http://aip.scitation.org/doi/pdf/10.1063/5.0190642
Reference15 articles.
1. S.A. Alsuhibany, S. Abdel-Khalek, A. Algarni, A. Fayomi, D. Gupta, V. Kumar, and R.F. Mansour, “Ensemble of deep learning based clinical decision support system for chronic kidney disease diagnosis in medical internet of things environment”, Computational Intelligence and Neuroscience, 2021.
2. Z. Fki, B. Ammar and M.B. Ayed, “Machine learning with internet of things data for risk prediction: application in ESRD”, In 12th International Conference on Research Challenges in Information Science (RCIS) (pp. 1–6). IEEE, 2018.
3. A diagnostic prediction model for chronic kidney disease in internet of things platform
4. A. Abdelaziz, A.S. Salama, A.M. Riad and A.N. Mahmoud, “A machine learning model for predicting of chronic kidney disease based internet of things and cloud computing in smart cities”, In Security in Smart Cities: Models, Applications, and Challenges (pp. 93–114). Springer, Cham, 2019.
5. B.V. Ravindra, N. Sriraam and M. Geetha, “Chronic kidney disease detection using back propagation neural network classifier”, In International Conference on Communication, Computing and Internet of Things (IC3IoT) (pp. 65–68). IEEE, 2018.
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