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Postgraduate Medicine Volume 134, 2022 - Issue 7
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Clinical Features - Original Research

Prediction of the severity of acute pancreatitis using machine learning models

You Zhoua Pancreatic Center, Department of Gastroenterology, Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, Jiangsu, China;b Yangzhou Key Laboratory of Pancreatic Disease, Institute of Digestive Diseases, Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, Jiangsu, ChinaORCID Iconhttps://orcid.org/0000-0002-1352-0211View further author information
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Fei Hana Pancreatic Center, Department of Gastroenterology, Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, Jiangsu, China;b Yangzhou Key Laboratory of Pancreatic Disease, Institute of Digestive Diseases, Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, Jiangsu, ChinaORCID Iconhttps://orcid.org/0000-0003-3914-1073View further author information
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Xiao-Lei Shia Pancreatic Center, Department of Gastroenterology, Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, Jiangsu, China;b Yangzhou Key Laboratory of Pancreatic Disease, Institute of Digestive Diseases, Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, Jiangsu, ChinaORCID Iconhttps://orcid.org/0000-0001-7617-4881View further author information
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Jun-Xian Zhanga Pancreatic Center, Department of Gastroenterology, Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, Jiangsu, China;b Yangzhou Key Laboratory of Pancreatic Disease, Institute of Digestive Diseases, Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, Jiangsu, ChinaORCID Iconhttps://orcid.org/0000-0003-4725-1854View further author information
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Guang-Yao Lia Pancreatic Center, Department of Gastroenterology, Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, Jiangsu, China;b Yangzhou Key Laboratory of Pancreatic Disease, Institute of Digestive Diseases, Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, Jiangsu, ChinaORCID Iconhttps://orcid.org/0000-0002-0067-7391View further author information
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Chen-Chen Yuana Pancreatic Center, Department of Gastroenterology, Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, Jiangsu, China;b Yangzhou Key Laboratory of Pancreatic Disease, Institute of Digestive Diseases, Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, Jiangsu, ChinaORCID Iconhttps://orcid.org/0000-0002-0551-0718View further author information
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Guo-Tao Lua Pancreatic Center, Department of Gastroenterology, Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, Jiangsu, China;b Yangzhou Key Laboratory of Pancreatic Disease, Institute of Digestive Diseases, Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, Jiangsu, ChinaORCID Iconhttps://orcid.org/0000-0002-8325-0405View further author information
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Liang-Hao Huc Department of Gastroenterology, First Affiliated Hospital of Naval Medical University, Shanghai, ChinaORCID Iconhttps://orcid.org/0000-0001-7535-7475View further author information
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Jia-Jia Panb Yangzhou Key Laboratory of Pancreatic Disease, Institute of Digestive Diseases, Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, Jiangsu, China;d Department of Intensive Care Unit, Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, Jiangsu, ChinaCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0003-4055-4131View further author information
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Wei-Ming Xiaoa Pancreatic Center, Department of Gastroenterology, Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, Jiangsu, China;b Yangzhou Key Laboratory of Pancreatic Disease, Institute of Digestive Diseases, Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, Jiangsu, ChinaCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-8893-9076View further author information
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Guang-Huai Yaoa Pancreatic Center, Department of Gastroenterology, Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, Jiangsu, China;b Yangzhou Key Laboratory of Pancreatic Disease, Institute of Digestive Diseases, Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, Jiangsu, ChinaCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-3055-3787View further author information
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Pages 703-710 | Received 27 Feb 2022, Accepted 07 Jun 2022, Published online: 12 Jul 2022

Citations (5)

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Hassam Ali, Faisal Inayat, Rubaid Dhillon, Pratik Patel, Arslan Afzal, Christin Wilkinson, Attiq Ur Rehman, Muhammad Sajeel Anwar, Gul Nawaz, Ahtshamullah Chaudhry, Junaid Rasul Awan, Muhammad Sohaib Afzal, Jayanta Samanta, Douglas G. Adler & Babu P. Mohan. (2024) Predicting the risk of early intensive care unit admission for patients hospitalized with acute pancreatitis using supervised machine learning. Baylor University Medical Center Proceedings 37:3, pages 437-447.
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Bo Li, Weiqing Wu, Aijun Liu, Lifeng Feng, Bin Li, Yong Mei, Li Tan, Chaoyang Zhang & Yangtao Tian. (2023) Establishment and Validation of a Nomogram Prediction Model for the Severe Acute Pancreatitis. Journal of Inflammation Research 16, pages 2831-2843.
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Articles from other publishers (3)

Rui Qian, Jiamei Zhuang, Jianjun Xie, Honghui Cheng, Haiya Ou, Xiang Lu & Zichen Ouyang. (2024) Predictive value of machine learning for the severity of acute pancreatitis: A systematic review and meta-analysis. Heliyon 10:8, pages e29603.
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Jian-Xiong Hu, Cheng-Fei Zhao, Shu-Ling Wang, Xiao-Yan Tu, Wei-Bin Huang, Jun-Nian Chen, Ying Xie & Cun-Rong Chen. (2023) Acute pancreatitis: A review of diagnosis, severity prediction and prognosis assessment from imaging technology, scoring system and artificial intelligence. World Journal of Gastroenterology 29:37, pages 5268-5291.
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Theddeus T. Akano & Chinemerem C. James. (2022) An assessment of ensemble learning approaches and single-based machine learning algorithms for the characterization of undersaturated oil viscosity. Beni-Suef University Journal of Basic and Applied Sciences 11:1.
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