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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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| Publicado no: | PLoS One |
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| Main Authors: | , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Public Library of Science
2018
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6235308/ https://ncbi.nlm.nih.gov/pubmed/30427908 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0207096 |
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