Multivariable prediction model of complications derived from diabetes mellitus using machine learning on scarce highly unbalanced data-Reference-Cited by-同舟云学术

Multivariable prediction model of complications derived from diabetes mellitus using machine learning on scarce highly unbalanced data

Published:2023-10-26 Issue: Volume: Page:
ISSN:0973-3930
Container-title:International Journal of Diabetes in Developing Countries
language:en
Short-container-title:Int J Diabetes Dev Ctries

Author:

Colmenares-Mejía Claudia C.^ORCID,Rincón-Acuña Juan C.^ORCID,Cely Andrés,González-Vélez Abel E.,Castillo Andrea,Murcia Jossie,Isaza-Ruget Mario A.^ORCID

Funder

Ministerio de Ciencia, Tecnología e Innovación

Publisher

Springer Science and Business Media LLC

Subject

Endocrinology, Diabetes and Metabolism,Internal Medicine

Link

https://link.springer.com/content/pdf/10.1007/s13410-023-01264-7.pdf

Reference18 articles.

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3. Zimmet P, Alberti KG, Magliano DJ, Bennett PH. Diabetes mellitus statistics on prevalence and mortality: facts and fallacies. Nat Rev Endocrinol. 2016;12:616–22. https://doi.org/10.1038/nrendo.2016.105.

4. Forbes JM, Cooper ME. Mechanisms of diabetic complications. Physiol Rev. 2013;93:137–88. https://doi.org/10.1152/physrev.00045.2011.

5. Tanaka S, Tanaka S, Iimuro S. Predicting macro- and microvascular complications in type 2 diabetes. Diabetes Care. 2013;36:1193–9. https://doi.org/10.2337/dc12-0958.