Short: Basal-Adjust: Trend Prediction Alerts and Adjusted Basal Rates for Hyperglycemia Prevention
Author:
Affiliation:
1. University of Virginia, Charlottesville, VA, USA
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3580252.3586987
Reference23 articles.
1. Giada Acciaroli John B. Welsh and Halis Kaan Akturk. 2022. Mitigation of Rebound Hyperglycemia With Real-Time Continuous Glucose Monitoring Data and Predictive Alerts. In Journal of Diabetes Science and Technology.
2. Muhammad Asad Usman Qamar and Muhammad Abbas. 2021. Blood Glucose Level Prediction of Diabetic Type 1 Patients Using Nonlinear Autoregressive Neural Networks. In Journal of Healthcare Engineering.
3. Dzmitry Bahdanau, KyungHyun Cho, and Yoshua Bengio. 2015. Neural Machine Translation By Jointly Learning To Align And Translate. International Conference on Learning Representation (2015).
4. Geremia B. Bolli, Irving S. Gottesman, Peter J. Campbell, Morey W. Haymond, Philip E. Cryer, and John E. Gerich. 1984. Glucose Counterregulation and Waning of Insulin in the Somogyi Phenomenon (Posthypoglycemic Hyperglycemia). New England Journal of Medicine (1984).
5. Six-Month Randomized, Multicenter Trial of Closed-Loop Control in Type 1 Diabetes
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