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 |
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