Identification of key factors for malnutrition diagnosis in chronic gastrointestinal diseases using machine learning underscores the importance of GLIM criteria as well as additional parameters

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Title:: Identification of key factors for malnutrition diagnosis in chronic gastrointestinal diseases using machine learning underscores the importance of GLIM criteria as well as additional parameters
Document type:: Zeitschriftenaufsatz
Author(s):: Rischmüller, Karen ; Caton, Vanessa ; Wolfien, Markus ; Ehlers, Luise ; van Welzen, Matti ; Brauer, David ; Sautter, Lea F. ; Meyer, Fatuma ; Valentini, Luzia ; Wiese, Mats L. ; Aghdassi, Ali A. ; Jaster, Robert ; Wolkenhauer, Olaf ; Lamprecht, Georg ; Bej, Saptarshi
Keywords:: Nutrition ; malnutrition ; GLIM criteria ; machine learning ; supervised and unsupervised learning ; decision trees ; gastrointestinal diseases ; liver cirrhosis
Journal title:: Frontiers in Nutrition
Year:: 2024
Journal volume:: 11
Fulltext / DOI:: doi:10.3389/fnut.2024.1479501
Publisher:: Frontiers Media S.A.
E-ISSN:: 2296-861X
Date of publication:: 12.12.2024
CC license:: by, https://creativecommons.org/licenses/by/4.0

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