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Machine learning-based identification of efficient and restrictive physiological subphenotypes in acute respiratory distress syndrome.

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Title: Machine learning-based identification of efficient and restrictive physiological subphenotypes in acute respiratory distress syndrome.
Authors: Meza-Fuentes, Gabriela1 (AUTHOR) gmezaf@udd.cl, Delgado, Iris2 (AUTHOR) idelgado@udd.cl, Barbé, Mario1 (AUTHOR) m.barbe@udd.cl, Sánchez-Barraza, Ignacio1 (AUTHOR) ignacioa.sanchezb@gmail.com, Retamal, Mauricio A.3 (AUTHOR) mretamal@udd.cl, López, René4,5 (AUTHOR) rene.lopez@udd.cl
Source: Intensive Care Medicine Experimental. 3/1/2025, Vol. 13 Issue 1, p1-11. 11p.
Database: Academic Search Ultimate
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  Data: Machine learning-based identification of efficient and restrictive physiological subphenotypes in acute respiratory distress syndrome.
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  Data: <searchLink fieldCode="JN" term="%22Intensive+Care+Medicine+Experimental%22">Intensive Care Medicine Experimental</searchLink>. 3/1/2025, Vol. 13 Issue 1, p1-11. 11p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=183374145
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1186/s40635-025-00737-9
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      – Code: eng
        Text: English
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        PageCount: 11
        StartPage: 1
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      – TitleFull: Machine learning-based identification of efficient and restrictive physiological subphenotypes in acute respiratory distress syndrome.
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            NameFull: Meza-Fuentes, Gabriela
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            NameFull: Delgado, Iris
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            NameFull: Barbé, Mario
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            NameFull: Sánchez-Barraza, Ignacio
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            NameFull: Retamal, Mauricio A.
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            NameFull: López, René
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            – D: 01
              M: 03
              Text: 3/1/2025
              Type: published
              Y: 2025
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