Research advances in machine learning models for acute pancreatitis

Minyue YIN; Jinzhou ZHU; Lu LIU; Jingwen GAO; Jiaxi LIN; Chunfang XU

doi:10.3969/j.issn.1001-5256.2023.12.034

Volume 39 Issue 12

Dec. 2023

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Article Navigation > Journal of Clinical Hepatology > 2023 > 39(12): 2978-2984

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Research advances in machine learning models for acute pancreatitis

DOI: 10.3969/j.issn.1001-5256.2023.12.034

Department of Gastroenterology，The First Affiliated Hospital of Soochow University，Suzhou，Jiangsu 215000，China

Research funding:

National Natural Science Foundation of China (82000540);

Science and Technology Plan of Suzhou City (SKY2021038)

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Corresponding author: XU Chunfang， xcf601@163.com （ORCID： 0000-0001-5648-3003）
Received Date: 2023-04-02
Accepted Date: 2023-05-06
Published Date: 2023-12-12

Abstract

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.
- Acute Pancreatitis,
- Artificial Intelligence,
- Supervised Machine Learning,
- Unsupervised Machine Learning

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References(45)

References

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Research advances in machine learning models for acute pancreatitis

DOI: 10.3969/j.issn.1001-5256.2023.12.034

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Research advances in machine learning models for acute pancreatitis

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