Acute kidney injury is a common and critical complication in patients with community-acquired pneumonia who are admitted to intensive care units, substantially increasing their risk of short-term mortality. To enhance early clinical decision-making, ...
Continuous renal replacement therapy (CRRT) is a vital intervention for critically ill patients with severe acute kidney injury, yet no standardized criteria exist to determine the optimal time for its discontinuation. We developed and validated mach...
BACKGROUND: Renal injury is a severe complication among individuals diagnosed with gout. This research constructed a machine learning predictive model to assess renal injury risk in gout patients.
Acute kidney injury is a common and severe complication following total hip arthroplasty, particularly in elderly or high-risk patients with chronic conditions, significantly increasing morbidity and mortality rates. Traditional prediction methods of...
Acute kidney injury (AKI) is a frequent and severe complication in intensive care unit (ICU) patients with respiratory failure, associated with high mortality, prolonged hospitalization, and substantial healthcare burden. Conventional risk scores, su...
BMC medical informatics and decision making
Oct 10, 2025
OBJECTIVE: To develop and evaluate machine learning models combined with survival analysis for predicting 7-, 14-, and 28-day mortality in critically ill children with acute kidney injury (AKI), identifying key predictors to guide risk stratification...
BACKGROUND: Sepsis-associated acute kidney injury (SA-AKI) is a frequent and life-threatening complication in patients in the intensive care unit (ICU), significantly increasing both mortality rates and the risk of chronic kidney dysfunction. However...
Electronic health records contain multimodal data that can inform clinical decisions but are often unsuited for advanced machine learning analyses due to lack of labeled data. Here, we present InfEHR, a framework to automatically compute clinical lik...
The primary objective of this study is to employ machine learning (ML) algorithms to develop predictive models for renal function recovery in critically ill patients undergoing continuous renal replacement therapy (CRRT) due to acute kidney injury (...
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