Artificial Intelligence in Acute Kidney Injury Risk Prediction
Joana Gameiro, Tiago Branco, José António Lopes
Abstract
Acute kidney injury (AKI) is a frequent complication in hospitalized patients, which is associated with worse short and long-term outcomes. It is crucial to develop methods to identify patients at risk for AKI and to diagnose subclinical AKI in order to improve patient outcomes. The advances in clinical informatics and the increasing availability of electronic medical records have allowed for the development of artificial intelligence predictive models of risk estimation in AKI. In this review, we discussed the progress of AKI risk prediction from risk scores to electronic alerts to machine learning methods.
Topics & Concepts
MedicineAcute kidney injurySubclinical infectionIntensive care medicineInformaticsRisk assessmentMedical recordMedical emergencyInternal medicineEngineeringComputer scienceElectrical engineeringComputer securityAcute Kidney Injury ResearchChronic Kidney Disease and DiabetesTrauma, Hemostasis, Coagulopathy, Resuscitation