ORAKLE: Optimal Risk prediction for mAke30 in patients with sepsis associated AKI using deep LEarning
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DOI: 10.1186/s13054-025-05457-w
Abstract: Major Adverse Kidney Events within 30 days (MAKE30) is an important patient-centered outcome for assessing the impact of acute kidney injury (AKI). Existing prediction models for MAKE30 are static and overlook dynamic changes in clinical… read more here.
Keywords: deep learning; make30; eicu crd; patients sepsis ... See more keywords
Major Adverse Kidney Events in Hospitalized Older Patients With Acute Kidney Injury: Machine Learning–Based Model Development and Validation Study
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DOI: 10.2196/52786
Abstract: Background Acute kidney injury (AKI) is a common complication in hospitalized older patients, associated with increased morbidity, mortality, and health care costs. Major adverse kidney events within 30 days (MAKE30), a composite of death, new… read more here.
Keywords: make30; older patients; model; hospitalized older ... See more keywords