TITLE

USING MACHINE LEARNING TO PREDICT SEVERITY IN ACUTE PANCREATITIS

PUB. DATE
April 2004
SOURCE
Gut;Apr2004 Supplement 3, Vol. 53, pA122
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Acute pancreatitis (AP) has a very variable course. Accurate early prediction of severity is useful to direct clinical care and to stratify patients for trials. Current assessment toots are inaccurate and unable to adapt to new parameters. None of the current systems uses C-reactive protein (CRP). These problems can be overcome using modern machine learning tools. This system for the first time combines scoring of systemic disturbance and admission CRP value for the prediction of severe AP. The score is simple to use, and more accurate than admission APACHE-II.
ACCESSION #
13219289

 

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