Cloud-Based Healthcare Architecture for Diabetes Patients Using Machine Learning
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-42511-0_52
Reference15 articles.
1. Azbeg, K., Boudhane, M., Ouchetto, O., & Jai Andaloussi, S. (2022). Diabetes emergency cases identification based on a statistical predictive model. Journal of Big Data, 9(1). https://doi.org/10.1186/s40537-022-00582-7
2. Bogatyrev, S. N. (2016). Physical activity and type 2 diabetes mellitus risk: Population studies review. Diabetes Mellitus, 19(6), 486–493. https://doi.org/10.14341/DM8030
3. Bonds, J. A., Hart, P. C., Minshall, R. D., Lazarov, O., Haus, J. M., & Bonini, M. G. (2016). Type 2 diabetes mellitus as a risk factor for Alzheimer’s disease. Genes, Environment and Alzheimer’s Disease, 387–413. https://doi.org/10.1016/B978-0-12-802851-3.00013-9
4. Cho, N. H., Shaw, J. E., Karuranga, S., Huang, Y., da Rocha Fernandes, J. D., Ohlrogge, A. W., & Malanda, B. (2018). IDF diabetes Atlas: Global estimates of diabetes prevalence for 2017 and projections for 2045. Diabetes Research and Clinical Practice, 138, 271–281. https://doi.org/10.1016/j.diabres.2018.02.023
5. Gourisaria, M. K., Jee, G., Harshvardhan, G. M., Singh, V., Singh, P. K., & Workneh, T. C. (2022). Data science appositeness in diabetes mellitus diagnosis for healthcare systems of developing nations. IET Communications, 16(5), 532–547. https://doi.org/10.1049/cmu2.12338
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