A systematic review of machine learning-based prognostic models for acute pancreatitis: Towards improving methods and reporting quality.

A systematic review of machine learning-based prognostic models for acute pancreatitis: Towards improving methods and reporting quality.

<h4>Background</h4>An accurate prognostic tool is essential to aid clinical decision-making (e.g., patient triage) and to advance personalized medicine. However, such a prognostic tool is lacking for acute pancreatitis (AP). Increasingly machine learning (ML) techniques are being used to...

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Main Authors: Brian Critelli, Amier Hassan, Ila Lahooti, Lydia Noh, Jun Sung Park, Kathleen Tong, Ali Lahooti, Nathan Matzko, Jan Niklas Adams, Lukas Liss, Justin Quion, David Restrepo, Melica Nikahd, Stacey Culp, Adam Lacy-Hulbert, Cate Speake, James Buxbaum, Jason Bischof, Cemal Yazici, Anna Evans-Phillips, Sophie Terp, Alexandra Weissman, Darwin Conwell, Philip Hart, Mitchell Ramsey, Somashekar Krishna, Samuel Han, Erica Park, Raj Shah, Venkata Akshintala, John A Windsor, Nikhil K Mull, Georgios Papachristou, Leo Anthony Celi, Peter Lee
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2025-02-01
Series:PLoS Medicine
Online Access:https://doi.org/10.1371/journal.pmed.1004432
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https://doi.org/10.1371/journal.pmed.1004432

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