Development and validation of a prognostic prediction model for patients with traumatic multiple fractures and hemorrhagic shock using an Automated Machine Learning framework: a retrospective cohort study.
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| Title: | Development and validation of a prognostic prediction model for patients with traumatic multiple fractures and hemorrhagic shock using an Automated Machine Learning framework: a retrospective cohort study. |
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| Authors: | Han T; Department of Emergency, Ya'an Polytechnic College Affiliated Hospital, Ya'an, Sichuan, China., Li Y; Faculty of Clinical Medicine, Ya'an Polytechnic College, Ya'an, Sichuan, China., Mu X; Department of Emergency, Ya'an People's Hospital, Ya'an, Sichuan, China., Wu P; Department of Emergency, Yucheng District People's Hospital of Ya'an, Ya'an, Sichuan, China., Zhang Z; Department of Emergency, Mingshan District People's Hospital of Ya'an, Ya'an, Sichuan, China., Zhang L; Department of Emergency, Ya'an Hospital of Traditional Chinese Medicine, Ya'an, Sichuan, China., Liang Z; Department of Surgery, Ya'an Renkang Hospital, Ya'an, Sichuan, China., Li L; Department of Emergency and Critical Care Medicine, The 945th Hospital of the Joint Logistics Support Force of the Chinese People's Liberation Army, Ya'an, Sichuan, China. |
| Source: | Frontiers in medicine [Front Med (Lausanne)] 2026 Jun 10; Vol. 13, pp. 1837872. Date of Electronic Publication: 2026 Jun 10 (Print Publication: 2026). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Frontiers Media S.A Country of Publication: Switzerland NLM ID: 101648047 Publication Model: eCollection Cited Medium: Print ISSN: 2296-858X (Print) Linking ISSN: 2296858X NLM ISO Abbreviation: Front Med (Lausanne) Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 42359088 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Development and validation of a prognostic prediction model for patients with traumatic multiple fractures and hemorrhagic shock using an Automated Machine Learning framework: a retrospective cohort study. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Han+T%22">Han T</searchLink>; Department of Emergency, Ya'an Polytechnic College Affiliated Hospital, Ya'an, Sichuan, China.<br /><searchLink fieldCode="AU" term="%22Li+Y%22">Li Y</searchLink>; Faculty of Clinical Medicine, Ya'an Polytechnic College, Ya'an, Sichuan, China.<br /><searchLink fieldCode="AU" term="%22Mu+X%22">Mu X</searchLink>; Department of Emergency, Ya'an People's Hospital, Ya'an, Sichuan, China.<br /><searchLink fieldCode="AU" term="%22Wu+P%22">Wu P</searchLink>; Department of Emergency, Yucheng District People's Hospital of Ya'an, Ya'an, Sichuan, China.<br /><searchLink fieldCode="AU" term="%22Zhang+Z%22">Zhang Z</searchLink>; Department of Emergency, Mingshan District People's Hospital of Ya'an, Ya'an, Sichuan, China.<br /><searchLink fieldCode="AU" term="%22Zhang+L%22">Zhang L</searchLink>; Department of Emergency, Ya'an Hospital of Traditional Chinese Medicine, Ya'an, Sichuan, China.<br /><searchLink fieldCode="AU" term="%22Liang+Z%22">Liang Z</searchLink>; Department of Surgery, Ya'an Renkang Hospital, Ya'an, Sichuan, China.<br /><searchLink fieldCode="AU" term="%22Li+L%22">Li L</searchLink>; Department of Emergency and Critical Care Medicine, The 945th Hospital of the Joint Logistics Support Force of the Chinese People's Liberation Army, Ya'an, Sichuan, China. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22101648047%22">Frontiers in medicine</searchLink> [Front Med (Lausanne)] 2026 Jun 10; Vol. 13, pp. 1837872. <i>Date of Electronic Publication: </i>2026 Jun 10 (<i>Print Publication: </i>2026). – 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%2EA%22">Frontiers Media S.A </searchLink><i>Country of Publication: </i>Switzerland <i>NLM ID: </i>101648047 <i>Publication Model: </i>eCollection <i>Cited Medium: </i>Print <i>ISSN: </i>2296-858X (Print) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%222296858X%22">2296858X </searchLink><i>NLM ISO Abbreviation: </i>Front Med (Lausanne) <i>Subsets: </i>PubMed not MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=42359088 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3389/fmed.2026.1837872 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: 1837872 Titles: – TitleFull: Development and validation of a prognostic prediction model for patients with traumatic multiple fractures and hemorrhagic shock using an Automated Machine Learning framework: a retrospective cohort study. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Han T – PersonEntity: Name: NameFull: Li Y – PersonEntity: Name: NameFull: Mu X – PersonEntity: Name: NameFull: Wu P – PersonEntity: Name: NameFull: Zhang Z – PersonEntity: Name: NameFull: Zhang L – PersonEntity: Name: NameFull: Liang Z – PersonEntity: Name: NameFull: Li L IsPartOfRelationships: – BibEntity: Dates: – D: 10 M: 06 Text: 2026 Jun 10 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 2296-858X Numbering: – Type: volume Value: 13 Titles: – TitleFull: Frontiers in medicine Type: main |
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