Functional data analysis and prediction tools for continuous glucose-monitoring studies.

Gecili, Emrah; Huang, Rui; Khoury, Jane C; King, Eileen; Altaye, Mekibib; Bowers, Katherine; Szczesniak, Rhonda D

Gecili, Emrah; Huang, Rui; Khoury, Jane C; King, Eileen; Altaye, Mekibib; Bowers, Katherine; Szczesniak, Rhonda D.

Afiliação

Gecili E; Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
Huang R; Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
Khoury JC; Division of Statistics and Data Science, Department of Mathematical Sciences, University of Cincinnati, Cincinnati, OH, USA.
King E; Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
Altaye M; Division of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
Bowers K; Division of Endocrinology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
Szczesniak RD; Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.

J Clin Transl Sci ; 5(1): e51, 2020 Sep 22.

Article em En | MEDLINE | ID: mdl-33948272

Palavras-chave

Continuous glucose monitoring; functional data analysis; functional principal component analysis; glycemic excursion; hyperglycemia; hypoglycemia; real-time prediction

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Texto completo: 1 Bases de dados: MEDLINE Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Clin Transl Sci Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos

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