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Machine learning analysis of continuous glucose monitoring identifies a novel dysglycemic phenotype found in most people with cystic fibrosis.

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Title: Machine learning analysis of continuous glucose monitoring identifies a novel dysglycemic phenotype found in most people with cystic fibrosis.
Authors: Song J; Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA. Electronic address: stuart.song@duke.edu., Alvarez J; Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, USA., Gent A; Department of Surgery, Duke University School of Medicine, Durham, North Carolina, USA; Department of Anesthesiology, Duke University School of Medicine, Durham, North Carolina, USA., Gillespie S; Pediatric Biostatistics Core, Department of Pediatrics, Emory University School of Medicine, Atlanta, Georgia, USA., Harris RA; Georgia Prevention Institute, Medical College of Georgia, Augusta University, Augusta, Georgia, USA., McNeany J; Department of Pediatrics, Emory University School of Medicine, Atlanta, Georgia, USA., Daley T; Department of Pediatrics, Emory University School of Medicine, Atlanta, Georgia, USA., Kamaleswaran R; Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA; Department of Surgery, Duke University School of Medicine, Durham, North Carolina, USA; Department of Anesthesiology, Duke University School of Medicine, Durham, North Carolina, USA., Stecenko A; Department of Pediatrics, Emory University School of Medicine, Atlanta, Georgia, USA.
Source: Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society [J Cyst Fibros] 2026 May; Vol. 25 (3), pp. 474-481. Date of Electronic Publication: 2026 Apr 23.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Country of Publication: Netherlands NLM ID: 101128966 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-5010 (Electronic) Linking ISSN: 15691993 NLM ISO Abbreviation: J Cyst Fibros Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: <searchLink fieldCode="AU" term="%22Song+J%22">Song J</searchLink>; Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA. Electronic address: stuart.song@duke.edu.<br /><searchLink fieldCode="AU" term="%22Alvarez+J%22">Alvarez J</searchLink>; Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, USA.<br /><searchLink fieldCode="AU" term="%22Gent+A%22">Gent A</searchLink>; Department of Surgery, Duke University School of Medicine, Durham, North Carolina, USA; Department of Anesthesiology, Duke University School of Medicine, Durham, North Carolina, USA.<br /><searchLink fieldCode="AU" term="%22Gillespie+S%22">Gillespie S</searchLink>; Pediatric Biostatistics Core, Department of Pediatrics, Emory University School of Medicine, Atlanta, Georgia, USA.<br /><searchLink fieldCode="AU" term="%22Harris+RA%22">Harris RA</searchLink>; Georgia Prevention Institute, Medical College of Georgia, Augusta University, Augusta, Georgia, USA.<br /><searchLink fieldCode="AU" term="%22McNeany+J%22">McNeany J</searchLink>; Department of Pediatrics, Emory University School of Medicine, Atlanta, Georgia, USA.<br /><searchLink fieldCode="AU" term="%22Daley+T%22">Daley T</searchLink>; Department of Pediatrics, Emory University School of Medicine, Atlanta, Georgia, USA.<br /><searchLink fieldCode="AU" term="%22Kamaleswaran+R%22">Kamaleswaran R</searchLink>; Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA; Department of Surgery, Duke University School of Medicine, Durham, North Carolina, USA; Department of Anesthesiology, Duke University School of Medicine, Durham, North Carolina, USA.<br /><searchLink fieldCode="AU" term="%22Stecenko+A%22">Stecenko A</searchLink>; Department of Pediatrics, Emory University School of Medicine, Atlanta, Georgia, USA.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Elsevier%22">Elsevier </searchLink><i>Country of Publication: </i>Netherlands <i>NLM ID: </i>101128966 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1873-5010 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2215691993%22">15691993 </searchLink><i>NLM ISO Abbreviation: </i>J Cyst Fibros <i>Subsets: </i>MEDLINE
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        Value: 10.1016/j.jcf.2026.04.001
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        Text: English
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      – TitleFull: Machine learning analysis of continuous glucose monitoring identifies a novel dysglycemic phenotype found in most people with cystic fibrosis.
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              Text: 2026 May
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