This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (3229) Clinical Information and Decision Making (1915) Artificial Intelligence (2129) Machine Learning (2076) Decision Support for Health Professionals (1539) Development and Evaluation of Research Methods, Instruments and Tools (744)

Published on in Vol 7 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41577, first published .
Prediction of Next Glucose Measurement in Hospitalized Patients by Comparing Various Regression Methods: Retrospective Cohort Study

Prediction of Next Glucose Measurement in Hospitalized Patients by Comparing Various Regression Methods: Retrospective Cohort Study

Prediction of Next Glucose Measurement in Hospitalized Patients by Comparing Various Regression Methods: Retrospective Cohort Study

Authors of this article:

Andrew D Zale1 Author Orcid Image ;   Mohammed S Abusamaan1 Author Orcid Image ;   John McGready2 Author Orcid Image ;   Nestoras Mathioudakis1 Author Orcid Image
Article Authors Cited by (7) Tweetations (3) Metrics

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  2. Li Y, Shu Y, Wang G, Zhang W, Gao Z, Yan H, Xie P. The burden of cardiovascular disease in adolescents in China and globally due to sugar-sweetened beverage consumption from 1990 to 2021: results from the global burden of disease study 2021. BMC Public Health 2025;25(1) View
  3. Scheideman A, Shao M, Zelada H, Cuadros J, Foreman J, Sarder P, Ho C, Ejskjaer N, Fleischer J, Cichosz S, Armstrong D, Mathioudakis N, Wang T, Tham Y, Klonoff D. Machine Learning to Diagnose Complications of Diabetes. Journal of Diabetes Science and Technology 2025;19(6):1650 View
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