Research advances in machine learning models for acute pancreatitis

VernacularTitle:急性胰腺炎机器学习模型的研究进展
Author: Minyue YIN ¹ ; Jinzhou ZHU ¹ ; Lu LIU ¹ ; Jingwen GAO ¹ ; Jiaxi LIN ¹ ; Chunfang XU ¹
Author Information

1. Department of Gastroenterology， The First Affiliated Hospital of Soochow University， Suzhou， Jiangsu 215000， China
Publication Type:Review
Keywords: Acute Pancreatitis; Artificial Intelligence; Supervised Machine Learning; Unsupervised Machine Learning
From: Journal of Clinical Hepatology 2023;39(12):2978-2984
CountryChina
Language:Chinese
Abstract: Acute pancreatitis （AP） is a gastrointestinal disease that requires early intervention， and when it progresses to moderate-severe AP （MSAP） or severe AP （SAP）， there will be a significant increase in the mortality rate of patients. Machine learning （ML） has achieved great success in the early prediction of AP using clinical data with the help of its powerful computational and learning capabilities. This article reviews the research advances in ML in predicting the severity， complications， and death of AP， so as to provide a theoretical basis and new insights for clinical diagnosis and treatment of AP through artificial intelligence.