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| http://dx.doi.org/10.3389/fnut.2024.1516811 | DOI Listing |
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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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Department of Systems Biology and Bioinformatics, Institute of Computer Science, University of Rostock, Rostock, Germany.
Introduction: Disease-related malnutrition is common but often underdiagnosed in patients with chronic gastrointestinal diseases, such as liver cirrhosis, short bowel and intestinal insufficiency, and chronic pancreatitis. To improve malnutrition diagnosis in these patients, an evaluation of the current Global Leadership Initiative on Malnutrition (GLIM) diagnostic criteria, and possibly the implementation of additional criteria, is needed.
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Department of Orthopedics, Government Medical College, Omandurar Government Estate, Tamil Nadu, Chennai 600002, India.
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