Subphenotyping prone position responders with machine learning.

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Bibliographic Details
Title: Subphenotyping prone position responders with machine learning.
Authors: Fosset M; Department of Anesthesia, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.; Center for Anesthesia Research Excellence (CARE), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.; Medical Intensive Care Unit and PhyMedExp, Lapeyronie Montpellier University Hospital, Lapeyronie Teaching Hospital, University Montpellier, 1; 371 Avenue Du Doyen Gaston Giraud, 34090, Montpellier, CEDEX 5, France.; Desbrest Institute of Epidemiology and Public Health, University of Montpellier, INRIA, Montpellier, France., von Wedel D; Department of Anesthesia, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.; Center for Anesthesia Research Excellence (CARE), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.; Institute of Medical Informatics, Charité-Universitätsmedizin Berlin, Berlin, Germany., Redaelli S; Department of Anesthesia, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.; Center for Anesthesia Research Excellence (CARE), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.; School of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy.; Department of Anesthesiology, Perioperative and Pain Medicine, Lahey Hospital and Medical Center, Burlington, MA, USA., Talmor D; Department of Anesthesia, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.; Center for Anesthesia Research Excellence (CARE), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA., Molinari N; Desbrest Institute of Epidemiology and Public Health, University of Montpellier, INRIA, Montpellier, France., Josse J; Desbrest Institute of Epidemiology and Public Health, University of Montpellier, INRIA, Montpellier, France., Baedorf-Kassis EN; Department of Pulmonary, Critical Care and Sleep Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA., Schaefer MS; Department of Anesthesia, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.; Center for Anesthesia Research Excellence (CARE), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.; Department of Anesthesiology, Duesseldorf University Hospital, Duesseldorf, Germany., Jung B; Department of Anesthesia, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA. b-jung@chu-montpellier.fr.; Center for Anesthesia Research Excellence (CARE), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA. b-jung@chu-montpellier.fr.; Medical Intensive Care Unit and PhyMedExp, Lapeyronie Montpellier University Hospital, Lapeyronie Teaching Hospital, University Montpellier, 1; 371 Avenue Du Doyen Gaston Giraud, 34090, Montpellier, CEDEX 5, France. b-jung@chu-montpellier.fr.; Department of Pulmonary, Critical Care and Sleep Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA. b-jung@chu-montpellier.fr.
Source: Critical care (London, England) [Crit Care] 2025 Mar 14; Vol. 29 (1), pp. 116. Date of Electronic Publication: 2025 Mar 14.
Publication Type: Journal Article; Observational Study
Journal Info: Publisher: BioMed Central Ltd Country of Publication: England NLM ID: 9801902 Publication Model: Electronic Cited Medium: Internet ISSN: 1466-609X (Electronic) Linking ISSN: 13648535 NLM ISO Abbreviation: Crit Care Subsets: MEDLINE
Database: MEDLINE Ultimate
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Description
ISSN:1466-609X
DOI:10.1186/s13054-025-05340-8