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ABSTRACT: Purpose of review
Acute kidney injury (AKI) affects nearly 60% of all patients admitted to ICUs. Large volumes of clinical, monitoring and laboratory data produced in ICUs allow the application of artificial intelligence analytics. The purpose of this article is to assimilate and critically evaluate recently published literature regarding artificial intelligence applications for predicting, diagnosing and subphenotyping AKI among critically ill patients.Recent findings
Among recent studies regarding artificial intelligence implementations for predicting, diagnosing and subphenotyping AKI among critically ill patients, there are many promising models, but few had external validation, clinical interpretability and high predictive performance. Deep learning techniques leveragi
SUBMITTER: Ozrazgat-Baslanti T
PROVIDER: S-EPMC8783984 | biostudies-literature | 2021 Dec
REPOSITORIES: biostudies-literature