AUTHOR=Tan Zhaowang , Li Gaoxiang , Zheng Yueliang , Li Qian , Cai Wenwei , Tu Jianfeng , Jin Senjun 

TITLE=Advances in the clinical application of machine learning in acute pancreatitis: a review

JOURNAL=Frontiers in Medicine

VOLUME=Volume 11 - 2024

YEAR=2025

URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2024.1487271

DOI=10.3389/fmed.2024.1487271

ISSN=2296-858X

ABSTRACT=Traditional disease prediction models and scoring systems for acute pancreatitis (AP) are often inadequate in providing concise, reliable, and effective predictions regarding disease progression and prognosis. As a novel interdisciplinary field within artificial intelligence (AI), machine learning (ML) is increasingly being applied to various aspects of AP, including severity assessment, complications, recurrence rates, organ dysfunction, and the timing of surgical intervention. This review focuses on recent advancements in the application of ML models in the context of AP.