Author's reply: "An interpretable machine learning approach for predicting clinically important gastrointestinal bleeding in critically ill patients".
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| Title: | Author's reply: "An interpretable machine learning approach for predicting clinically important gastrointestinal bleeding in critically ill patients". |
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| Authors: | Ono S; Department of Anesthesiology and Critical Care Medicine, Jichi Medical University Saitama Medical Center, 1-847 Amanuma-cho, Omiya-ku, Saitama, Saitama 330-8503, Japan; Department of Emergency and Intensive Care Medicine, Tokyo Metropolitan Tama Medical Center, Tokyo, Japan. Electronic address: airness.of.mj@gmail.com. |
| Source: | Anaesthesia, critical care & pain medicine [Anaesth Crit Care Pain Med] 2026 May; Vol. 45 (3), pp. 101803. Date of Electronic Publication: 2026 Mar 03. |
| Publication Type: | Letter |
| Journal Info: | Publisher: Published by Elsevier Masson SAS on behalf of the Société française d'anesthésie et de réanimation (Sfar) Country of Publication: France NLM ID: 101652401 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2352-5568 (Electronic) Linking ISSN: 23525568 NLM ISO Abbreviation: Anaesth Crit Care Pain Med Subsets: MEDLINE; In Process |
| Database: | MEDLINE Ultimate |
| FullText | Text: Availability: 0 |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 41786026 AccessLevel: 2 PubType: Editorial & Opinion PubTypeId: editorialOpinion PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Author's reply: "An interpretable machine learning approach for predicting clinically important gastrointestinal bleeding in critically ill patients". – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Ono+S%22">Ono S</searchLink>; Department of Anesthesiology and Critical Care Medicine, Jichi Medical University Saitama Medical Center, 1-847 Amanuma-cho, Omiya-ku, Saitama, Saitama 330-8503, Japan; Department of Emergency and Intensive Care Medicine, Tokyo Metropolitan Tama Medical Center, Tokyo, Japan. Electronic address: airness.of.mj@gmail.com. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22101652401%22">Anaesthesia, critical care & pain medicine</searchLink> [Anaesth Crit Care Pain Med] 2026 May; Vol. 45 (3), pp. 101803. <i>Date of Electronic Publication: </i>2026 Mar 03. – Name: TypePub Label: Publication Type Group: TypPub Data: Letter – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Published+by+Elsevier+Masson+SAS+on+behalf+of+the+Société+française+d'anesthésie+et+de+réanimation+%28Sfar%29%22">Published by Elsevier Masson SAS on behalf of the Société française d'anesthésie et de réanimation (Sfar) </searchLink><i>Country of Publication: </i>France <i>NLM ID: </i>101652401 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2352-5568 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2223525568%22">23525568 </searchLink><i>NLM ISO Abbreviation: </i>Anaesth Crit Care Pain Med <i>Subsets: </i>MEDLINE; In Process |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=41786026 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.accpm.2026.101803 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: 101803 Titles: – TitleFull: Author's reply: "An interpretable machine learning approach for predicting clinically important gastrointestinal bleeding in critically ill patients". Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Ono S IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: 2026 May Type: published Y: 2026 Identifiers: – Type: issn-electronic Value: 2352-5568 Numbering: – Type: volume Value: 45 – Type: issue Value: 3 Titles: – TitleFull: Anaesthesia, critical care & pain medicine Type: main |
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