Published on in Vol 10, No 6 (2022): June
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/36958, first published
.
Predicting Risk of Hypoglycemia in Patients With Type 2 Diabetes by Electronic Health Record–Based Machine Learning: Development and Validation
Predicting Risk of Hypoglycemia in Patients With Type 2 Diabetes by Electronic Health Record–Based Machine Learning: Development and Validation
Journals
- Liu S, Schlesinger J, McCoy A, Reese T, Steitz B, Russo E, Koh B, Wright A. New onset delirium prediction using machine learning and long short-term memory (LSTM) in electronic health record. Journal of the American Medical Informatics Association 2022;30(1):120 View
- Zhang L, Yang L, Zhou Z. Data-based modeling for hypoglycemia prediction: Importance, trends, and implications for clinical practice. Frontiers in Public Health 2023;11 View
- Wang S, Zhang Y, Sun F, Xi K, Sun Z, Zheng X, Guo F, Zhong H, Yang M, Shao Y, Huang B, Dong M, Ni S, Sun L. Catalase-like nanozymes combined with hydrogel to facilitate wound healing by improving the microenvironment of diabetic ulcers. Materials & Design 2023;225:111557 View
- Zou X, Liu Y, Ji L. Review: Machine learning in precision pharmacotherapy of type 2 diabetes—A promising future or a glimpse of hope?. DIGITAL HEALTH 2023;9 View
Books/Policy Documents
- Harris Y, Reich D, Li X. Diabetes Management in Hospitalized Patients. View