Patient clusters based on HbA1c trajectories: A step toward individualized medicine in type 2 diabetes

AIMS: To identify clinically meaningful clusters of patients with similar glycated hemoglobin (HbA1c) trajectories among patients with type 2 diabetes. METHODS: A retrospective cohort study using unsupervised machine learning clustering methodologies to determine clusters of patients with similar lo...

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Detalles Bibliográficos
Autores principales: Karpati, Tomas, Leventer-Roberts, Maya, Feldman, Becca, Cohen-Stavi, Chandra, Raz, Itamar, Balicer, Ran
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6235308/
https://www.ncbi.nlm.nih.gov/pubmed/30427908
http://dx.doi.org/10.1371/journal.pone.0207096

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6235308/
https://www.ncbi.nlm.nih.gov/pubmed/30427908
http://dx.doi.org/10.1371/journal.pone.0207096

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