Supervised Machine Learning Model for Diabetic Students’ Glucose Levels Classification System
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-47718-8_35
Reference20 articles.
1. American Diabetes Association: Standards of medical care in Diabetes—2007. Diabetes Care 30(Suppl 1), S4–S41 (2007)
2. Ajjan, R., Slattery, D., Wright, E.: Continuous glucose monitoring: a brief review for primary care practitioners. Adv. Ther. 36, 579–596 (2019)
3. Persson, E., Persson, S., Gerdtham, U.G., Steen Carlsson, K.: Swedish childhood diabetes study group: Effect of type 1 diabetes on school performance in a dynamic world: new analysis exploring Swedish register data. Appl. Econ., 51(24), pp. 2606–2622 (2019)
4. Alotaibi, M., Joy, M.: Internet of things support system for diabetic students: an exploratory study. In: Arai, K. (eds). In: Proceedings of the Future Technologies Conference (FTC) 2022, Volume 2. FTC 2022 2022. Lecture Notes in Networks and Systems, 560. Springer, Cham (2023)
5. Almulla, S.K., Zaatar, O., Ahmed, H.S., Jarndal, A.: Smart Artificial-Intelligence based Self-Care-Device for diabetic patients. In 2022 Advances in Science and Engineering Technology International Conferences (ASET) pp. 1–5. IEEE (2022)
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