Development and external validation of an interpretable machine learning model for diagnosing coronary heart disease in patients with type 2 diabetes and MASLD.
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| Title: | Development and external validation of an interpretable machine learning model for diagnosing coronary heart disease in patients with type 2 diabetes and MASLD. |
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| Authors: | Deng C; Department of Endocrinology and Metabolism, Guangxi Academy of Medical Sciences and the People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China., Feng L; Department of Endocrinology and Metabolism, Guangxi Academy of Medical Sciences and the People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China., Li T; Department of Respiratory and Critical Care Medicine, Guangxi Hospital of the First Affiliated Hospital, Sun Yat-sen University, Nanning, Guangxi, China., Wei S; Clinical Research Center of Guangxi Academy of Medical Sciences, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China., Zhu H; Department of Clinical Laboratory, Nantong Sixth People's Hospital Affiliated to Shanghai University, Nantong, Jiangsu, China., Lu J; Department of Endocrinology and Metabolism, Guangxi Academy of Medical Sciences and the People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China. |
| Source: | Frontiers in endocrinology [Front Endocrinol (Lausanne)] 2026 May 15; Vol. 17, pp. 1830594. Date of Electronic Publication: 2026 May 15 (Print Publication: 2026). |
| Publication Type: | Journal Article; Validation Study |
| Journal Info: | Publisher: Frontiers Research Foundation] Country of Publication: Switzerland NLM ID: 101555782 Publication Model: eCollection Cited Medium: Print ISSN: 1664-2392 (Print) Linking ISSN: 16642392 NLM ISO Abbreviation: Front Endocrinol (Lausanne) Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 42222087 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Development and external validation of an interpretable machine learning model for diagnosing coronary heart disease in patients with type 2 diabetes and MASLD. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Deng+C%22">Deng C</searchLink>; Department of Endocrinology and Metabolism, Guangxi Academy of Medical Sciences and the People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China.<br /><searchLink fieldCode="AU" term="%22Feng+L%22">Feng L</searchLink>; Department of Endocrinology and Metabolism, Guangxi Academy of Medical Sciences and the People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China.<br /><searchLink fieldCode="AU" term="%22Li+T%22">Li T</searchLink>; Department of Respiratory and Critical Care Medicine, Guangxi Hospital of the First Affiliated Hospital, Sun Yat-sen University, Nanning, Guangxi, China.<br /><searchLink fieldCode="AU" term="%22Wei+S%22">Wei S</searchLink>; Clinical Research Center of Guangxi Academy of Medical Sciences, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China.<br /><searchLink fieldCode="AU" term="%22Zhu+H%22">Zhu H</searchLink>; Department of Clinical Laboratory, Nantong Sixth People's Hospital Affiliated to Shanghai University, Nantong, Jiangsu, China.<br /><searchLink fieldCode="AU" term="%22Lu+J%22">Lu J</searchLink>; Department of Endocrinology and Metabolism, Guangxi Academy of Medical Sciences and the People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22101555782%22">Frontiers in endocrinology</searchLink> [Front Endocrinol (Lausanne)] 2026 May 15; Vol. 17, pp. 1830594. <i>Date of Electronic Publication: </i>2026 May 15 (<i>Print Publication: </i>2026). – Name: TypePub Label: Publication Type Group: TypPub Data: Journal Article; Validation Study – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Frontiers+Research+Foundation]%22">Frontiers Research Foundation] </searchLink><i>Country of Publication: </i>Switzerland <i>NLM ID: </i>101555782 <i>Publication Model: </i>eCollection <i>Cited Medium: </i>Print <i>ISSN: </i>1664-2392 (Print) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2216642392%22">16642392 </searchLink><i>NLM ISO Abbreviation: </i>Front Endocrinol (Lausanne) <i>Subsets: </i>MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=42222087 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3389/fendo.2026.1830594 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: 1830594 Titles: – TitleFull: Development and external validation of an interpretable machine learning model for diagnosing coronary heart disease in patients with type 2 diabetes and MASLD. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Deng C – PersonEntity: Name: NameFull: Feng L – PersonEntity: Name: NameFull: Li T – PersonEntity: Name: NameFull: Wei S – PersonEntity: Name: NameFull: Zhu H – PersonEntity: Name: NameFull: Lu J IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 05 Text: 2026 May 15 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 1664-2392 Numbering: – Type: volume Value: 17 Titles: – TitleFull: Frontiers in endocrinology Type: main |
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