Chronobiologically-informed features from CGM data provide unique information for XGBoost prediction of longer-term glycemic dysregulation in 8,000 individuals with type-2 diabetes.
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| Title: | Chronobiologically-informed features from CGM data provide unique information for XGBoost prediction of longer-term glycemic dysregulation in 8,000 individuals with type-2 diabetes. |
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| Authors: | Burks JH; Shiu Chen - Gene Lay Department of Bioengineering, University of California San Diego, La Jolla, California, United States of America., Joe L; Halicioğlu Data Science Institute, University of California San Diego, La Jolla, California, United States of America., Kanjaria K; Halicioğlu Data Science Institute, University of California San Diego, La Jolla, California, United States of America., Monsivais C; Halicioğlu Data Science Institute, University of California San Diego, La Jolla, California, United States of America., O'laughlin K; Halicioğlu Data Science Institute, University of California San Diego, La Jolla, California, United States of America., Smarr BL; Shiu Chen - Gene Lay Department of Bioengineering, University of California San Diego, La Jolla, California, United States of America.; Halicioğlu Data Science Institute, University of California San Diego, La Jolla, California, United States of America. |
| Source: | PLOS digital health [PLOS Digit Health] 2025 Apr 09; Vol. 4 (4), pp. e0000815. Date of Electronic Publication: 2025 Apr 09 (Print Publication: 2025). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: PLOS Country of Publication: United States NLM ID: 9918335064206676 Publication Model: eCollection Cited Medium: Internet ISSN: 2767-3170 (Electronic) Linking ISSN: 27673170 NLM ISO Abbreviation: PLOS Digit Health Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
| FullText | Text: Availability: 0 |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 40202975 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Chronobiologically-informed features from CGM data provide unique information for XGBoost prediction of longer-term glycemic dysregulation in 8,000 individuals with type-2 diabetes. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Burks+JH%22">Burks JH</searchLink>; Shiu Chen - Gene Lay Department of Bioengineering, University of California San Diego, La Jolla, California, United States of America.<br /><searchLink fieldCode="AU" term="%22Joe+L%22">Joe L</searchLink>; Halicioğlu Data Science Institute, University of California San Diego, La Jolla, California, United States of America.<br /><searchLink fieldCode="AU" term="%22Kanjaria+K%22">Kanjaria K</searchLink>; Halicioğlu Data Science Institute, University of California San Diego, La Jolla, California, United States of America.<br /><searchLink fieldCode="AU" term="%22Monsivais+C%22">Monsivais C</searchLink>; Halicioğlu Data Science Institute, University of California San Diego, La Jolla, California, United States of America.<br /><searchLink fieldCode="AU" term="%22O'laughlin+K%22">O'laughlin K</searchLink>; Halicioğlu Data Science Institute, University of California San Diego, La Jolla, California, United States of America.<br /><searchLink fieldCode="AU" term="%22Smarr+BL%22">Smarr BL</searchLink>; Shiu Chen - Gene Lay Department of Bioengineering, University of California San Diego, La Jolla, California, United States of America.; Halicioğlu Data Science Institute, University of California San Diego, La Jolla, California, United States of America. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%229918335064206676%22">PLOS digital health</searchLink> [PLOS Digit Health] 2025 Apr 09; Vol. 4 (4), pp. e0000815. <i>Date of Electronic Publication: </i>2025 Apr 09 (<i>Print Publication: </i>2025). – Name: TypePub Label: Publication Type Group: TypPub Data: Journal Article – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22PLOS%22">PLOS </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>9918335064206676 <i>Publication Model: </i>eCollection <i>Cited Medium: </i>Internet <i>ISSN: </i>2767-3170 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2227673170%22">27673170 </searchLink><i>NLM ISO Abbreviation: </i>PLOS Digit Health <i>Subsets: </i>PubMed not MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=40202975 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1371/journal.pdig.0000815 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: e0000815 Titles: – TitleFull: Chronobiologically-informed features from CGM data provide unique information for XGBoost prediction of longer-term glycemic dysregulation in 8,000 individuals with type-2 diabetes. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Burks JH – PersonEntity: Name: NameFull: Joe L – PersonEntity: Name: NameFull: Kanjaria K – PersonEntity: Name: NameFull: Monsivais C – PersonEntity: Name: NameFull: O'laughlin K – PersonEntity: Name: NameFull: Smarr BL IsPartOfRelationships: – BibEntity: Dates: – D: 09 M: 04 Text: 2025 Apr 09 Type: published Y: 2025 Identifiers: – Type: issn-electronic Value: 2767-3170 Numbering: – Type: volume Value: 4 – Type: issue Value: 4 Titles: – TitleFull: PLOS digital health Type: main |
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