Comparative analysis develops prediction models for acute kidney injury in ACLF patients, indicating potential for improved early identification.
Background Acute kidney injury (AKI) is one of the serious complications in acute-on-chronic liver failure (ACLF), and the mortality rate is very high. Early identification of high-risk patients is critical. Therefore, this study aimed to develop prediction models for AKI in ACLF patients based on machine learning (ML) algorithms.
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Zhang et al. (2025) studied this question.
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