View in EDS HTML Full Text PDF Full Text

Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults.

Saved in:
Bibliographic Details
Title: Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults.
Authors: ShangGuan Y; Department of Exercise Physiology, Kunsan National University, Gunsan, Republic of Korea., Ji K; Department of Clinical Medical Research, Binhai County People's Hospital, Binhai Clinical College, Yangzhou University Medical College, Yancheng, Jiangsu, China.; College of Biomedicine and Health, Huazhong Agricultural University, Wuhan, Hubei, China., Lin Z; Department of Exercise Physiology, Kunsan National University, Gunsan, Republic of Korea., He C; Department of Rehabilitation Medicine, Shantou University Medical College/Shenzhen Children's Hospital, Shantou, Guangdong, China., Sim YJ; Department of Exercise Physiology, Kunsan National University, Gunsan, Republic of Korea., Liu H; Department of Epidemiology and Biostatistics, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, Shaanxi, China., Huang K; Department of Health and Physical Education, The Education University of Hong Kong, Tai Po, Hong Kong SAR, China., Wu K; Department of Exercise Physiology, Kunsan National University, Gunsan, Republic of Korea., Yan L; Department of Articular Orthopedics, The First People's Hospital of Changzhou, The Third Affiliated Hospital of Soochow University, Changzhou, China., Xu K; Department of Endocrinology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China., Li H; Department of Articular Orthopedics, The First People's Hospital of Changzhou, The Third Affiliated Hospital of Soochow University, Changzhou, China.
Source: Frontiers in nutrition [Front Nutr] 2025 Nov 17; Vol. 12, pp. 1666477. Date of Electronic Publication: 2025 Nov 17 (Print Publication: 2025).
Publication Type: Journal Article
Journal Info: Publisher: Frontiers Media S. A Country of Publication: Switzerland NLM ID: 101642264 Publication Model: eCollection Cited Medium: Print ISSN: 2296-861X (Print) Linking ISSN: 2296861X NLM ISO Abbreviation: Front Nutr Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: mdl
DbLabel: MEDLINE Ultimate
An: 41334340
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22ShangGuan+Y%22">ShangGuan Y</searchLink>; Department of Exercise Physiology, Kunsan National University, Gunsan, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Ji+K%22">Ji K</searchLink>; Department of Clinical Medical Research, Binhai County People's Hospital, Binhai Clinical College, Yangzhou University Medical College, Yancheng, Jiangsu, China.; College of Biomedicine and Health, Huazhong Agricultural University, Wuhan, Hubei, China.<br /><searchLink fieldCode="AU" term="%22Lin+Z%22">Lin Z</searchLink>; Department of Exercise Physiology, Kunsan National University, Gunsan, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22He+C%22">He C</searchLink>; Department of Rehabilitation Medicine, Shantou University Medical College/Shenzhen Children's Hospital, Shantou, Guangdong, China.<br /><searchLink fieldCode="AU" term="%22Sim+YJ%22">Sim YJ</searchLink>; Department of Exercise Physiology, Kunsan National University, Gunsan, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Liu+H%22">Liu H</searchLink>; Department of Epidemiology and Biostatistics, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, Shaanxi, China.<br /><searchLink fieldCode="AU" term="%22Huang+K%22">Huang K</searchLink>; Department of Health and Physical Education, The Education University of Hong Kong, Tai Po, Hong Kong SAR, China.<br /><searchLink fieldCode="AU" term="%22Wu+K%22">Wu K</searchLink>; Department of Exercise Physiology, Kunsan National University, Gunsan, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Yan+L%22">Yan L</searchLink>; Department of Articular Orthopedics, The First People's Hospital of Changzhou, The Third Affiliated Hospital of Soochow University, Changzhou, China.<br /><searchLink fieldCode="AU" term="%22Xu+K%22">Xu K</searchLink>; Department of Endocrinology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.<br /><searchLink fieldCode="AU" term="%22Li+H%22">Li H</searchLink>; Department of Articular Orthopedics, The First People's Hospital of Changzhou, The Third Affiliated Hospital of Soochow University, Changzhou, China.
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22101642264%22">Frontiers in nutrition</searchLink> [Front Nutr] 2025 Nov 17; Vol. 12, pp. 1666477. <i>Date of Electronic Publication: </i>2025 Nov 17 (<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="%22Frontiers+Media+S%2E+A%22">Frontiers Media S. A </searchLink><i>Country of Publication: </i>Switzerland <i>NLM ID: </i>101642264 <i>Publication Model: </i>eCollection <i>Cited Medium: </i>Print <i>ISSN: </i>2296-861X (Print) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%222296861X%22">2296861X </searchLink><i>NLM ISO Abbreviation: </i>Front Nutr <i>Subsets: </i>PubMed not MEDLINE
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=41334340
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.3389/fnut.2025.1666477
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        StartPage: 1666477
    Titles:
      – TitleFull: Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: ShangGuan Y
      – PersonEntity:
          Name:
            NameFull: Ji K
      – PersonEntity:
          Name:
            NameFull: Lin Z
      – PersonEntity:
          Name:
            NameFull: He C
      – PersonEntity:
          Name:
            NameFull: Sim YJ
      – PersonEntity:
          Name:
            NameFull: Liu H
      – PersonEntity:
          Name:
            NameFull: Huang K
      – PersonEntity:
          Name:
            NameFull: Wu K
      – PersonEntity:
          Name:
            NameFull: Yan L
      – PersonEntity:
          Name:
            NameFull: Xu K
      – PersonEntity:
          Name:
            NameFull: Li H
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 17
              M: 11
              Text: 2025 Nov 17
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 2296-861X
          Numbering:
            – Type: volume
              Value: 12
          Titles:
            – TitleFull: Frontiers in nutrition
              Type: main
ResultId 1