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Use of classification and regression tree (CART), to identify hemoglobin A1C (HbA(1C)) cut-off thresholds predictive of poor tuberculosis treatment outcomes and associated risk factors
BACKGROUND: Rifampin-based therapy potentially exacerbates glycemic control among TB patients who are already at high risk of hyperglycemia. This impacts negatively to the optimal care of TB- diabetes mellitus co-affected patients. Classification and regression tree (CART), a machine-learning algori...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6830151/ https://www.ncbi.nlm.nih.gov/pubmed/31720385 http://dx.doi.org/10.1016/j.jctube.2018.01.002 |