Clustering for a better prediction of type 2 diabetes mellitus
Author:
Publisher
Springer Science and Business Media LLC
Subject
Endocrinology,Endocrinology, Diabetes and Metabolism
Link
http://www.nature.com/articles/s41574-021-00475-4.pdf
Reference8 articles.
1. American Diabetes Association. 2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2021. Diabetes Care 44 (Suppl. 1), 15–33 (2021).
2. Gourgari, E., Wilhelm, E. E., Hassanzadeh, H., Aroda, V. R. & Shoulson, I. A comprehensive review of the FDA-approved labels of diabetes drugs: Indications, safety, and emerging cardiovascular safety data. J. Diabetes Complications 31, 1719–1727 (2017).
3. Tabák, A. G. et al. Trajectories of glycaemia, insulin sensitivity, and insulin secretion before diagnosis of type 2 diabetes: an analysis from the Whitehall II study. Lancet 373, 2215–2221 (2009).
4. Ahlqvist, E. et al. Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. Lancet Diabetes Endocrinol. 6, 361–369 (2018).
5. Udler, M. S. et al. Type 2 diabetes genetic loci informed by multi-trait associations point to disease mechanisms and subtypes: A soft clustering analysis. PLoS Med. 15, e1002654 (2018).
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