Automated machine learning for early prediction of acute kidney injury in acute pancreatitis

Automated machine learning for early prediction of acute kidney injury in acute pancreatitis

Abstract Background Acute kidney injury (AKI) represents a frequent and grave complication associated with acute pancreatitis (AP), substantially elevating both mortality rates and the financial burden of hospitalization. The aim of our study is to construct a predictive model utilizing automated ma...

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Bibliographic Details
Main Authors: Rufa Zhang, Minyue Yin, Anqi Jiang, Shihou Zhang, Xiaodan Xu, Luojie Liu
Format: Article
Language:English
Published: BMC 2024-01-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Automated machine learning
Acute kidney injury
Acute pancreatitis
Creatinine
International normalized ratio
Predictive models
Online Access:https://doi.org/10.1186/s12911-024-02414-5

Internet

https://doi.org/10.1186/s12911-024-02414-5

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