Evaluating a machine learning tool for predicting hospital-acquired acute kidney injury
Hospital-acquired acute kidney injury (HA-AKI) is a common complication in hospitalized patients that can lead to chronic kidney disease and is associated with longer hospital stays, higher health care costs and increased mortality. Given these negative consequences, preventing HA-AKI can improve hospitalized patient outcomes. However, anticipating HA-AKI onset is difficult due to a large number …
