Machine learning and SHAP-based identification of RNASE1 linking environmental endocrine-disrupting chemicals exposure to atherosclerosis.
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| Title: | Machine learning and SHAP-based identification of RNASE1 linking environmental endocrine-disrupting chemicals exposure to atherosclerosis. |
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| Authors: | Zhou X; Department of Thoracic and Cardiovascular Surgery, Pingxiang People's Hospital, Pingxiang, China., Xiao Q; Department of Thoracic and Cardiovascular Surgery, Pingxiang People's Hospital, Pingxiang, China., Guo X; Department of Thoracic Surgery, Ganzhou Cancer Hospital, Ganzhou, China., Wang W; The First Clinical Medical College of Gannan Medical University, Ganzhou, China., Huang M; Department of Thoracic Surgery, The First Affiliated Hospital of Gannan Medical University, Ganzhou, China. |
| Source: | Medicine [Medicine (Baltimore)] 2025 Sep 12; Vol. 104 (37), pp. e44567. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Lippincott Williams & Wilkins Country of Publication: United States NLM ID: 2985248R Publication Model: Print Cited Medium: Internet ISSN: 1536-5964 (Electronic) Linking ISSN: 00257974 NLM ISO Abbreviation: Medicine (Baltimore) Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| FullText | Text: Availability: 0 |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 40958282 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Machine learning and SHAP-based identification of RNASE1 linking environmental endocrine-disrupting chemicals exposure to atherosclerosis. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Zhou+X%22">Zhou X</searchLink>; Department of Thoracic and Cardiovascular Surgery, Pingxiang People's Hospital, Pingxiang, China.<br /><searchLink fieldCode="AU" term="%22Xiao+Q%22">Xiao Q</searchLink>; Department of Thoracic and Cardiovascular Surgery, Pingxiang People's Hospital, Pingxiang, China.<br /><searchLink fieldCode="AU" term="%22Guo+X%22">Guo X</searchLink>; Department of Thoracic Surgery, Ganzhou Cancer Hospital, Ganzhou, China.<br /><searchLink fieldCode="AU" term="%22Wang+W%22">Wang W</searchLink>; The First Clinical Medical College of Gannan Medical University, Ganzhou, China.<br /><searchLink fieldCode="AU" term="%22Huang+M%22">Huang M</searchLink>; Department of Thoracic Surgery, The First Affiliated Hospital of Gannan Medical University, Ganzhou, China. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%222985248R%22">Medicine</searchLink> [Medicine (Baltimore)] 2025 Sep 12; Vol. 104 (37), pp. e44567. – 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="%22Lippincott+Williams+%26+Wilkins%22">Lippincott Williams & Wilkins </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>2985248R <i>Publication Model: </i>Print <i>Cited Medium: </i>Internet <i>ISSN: </i>1536-5964 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2200257974%22">00257974 </searchLink><i>NLM ISO Abbreviation: </i>Medicine (Baltimore) <i>Subsets: </i>MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=40958282 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1097/MD.0000000000044567 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: e44567 Titles: – TitleFull: Machine learning and SHAP-based identification of RNASE1 linking environmental endocrine-disrupting chemicals exposure to atherosclerosis. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Zhou X – PersonEntity: Name: NameFull: Xiao Q – PersonEntity: Name: NameFull: Guo X – PersonEntity: Name: NameFull: Wang W – PersonEntity: Name: NameFull: Huang M IsPartOfRelationships: – BibEntity: Dates: – D: 12 M: 09 Text: 2025 Sep 12 Type: published Y: 2025 Identifiers: – Type: issn-electronic Value: 1536-5964 Numbering: – Type: volume Value: 104 – Type: issue Value: 37 Titles: – TitleFull: Medicine Type: main |
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