Data assimilation on mechanistic models of glucose metabolism predicts glycemic states in adolescents following bariatric surgery.

Richter, Lauren R; Albert, Benjamin I; Zhang, Linying; Ostropolets, Anna; Zitsman, Jeffrey L; Fennoy, Ilene; Albers, David J; Hripcsak, George

Richter, Lauren R; Albert, Benjamin I; Zhang, Linying; Ostropolets, Anna; Zitsman, Jeffrey L; Fennoy, Ilene; Albers, David J; Hripcsak, George.

Afiliação

Richter LR; Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, United States.
Albert BI; Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, United States.
Zhang L; Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, United States.
Ostropolets A; Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, United States.
Zitsman JL; Division of Pediatric Surgery, Department of Surgery, Columbia University Irving Medical Center, New York, NY, United States.
Fennoy I; Division of Pediatric Endocrinology, Metabolism, and Diabetes, Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, United States.
Albers DJ; Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, United States.
Hripcsak G; Department of Bioengineering, University of Colorado Anschutz Medical Campus, Aurora, CO, United States.

Front Physiol ; 13: 923704, 2022.

Article em En | MEDLINE | ID: mdl-36518108

Palavras-chave

bariatric surgery; data assimilation; machine learning; mechanistic models of glucose metabolism; obesity; pediatrics; type 2 diabetes

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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Physiol Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos

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