Acute kidney injury (AKI) is now recognized as a heterogeneous syndrome that not only
affects acute morbidity and mortality, but also a patient's long-term prognosis. In this …

Kidney pathophysiology is often complex, nonlinear and heterogeneous, which limits the
utility of hypothetical-deductive reasoning and linear, statistical approaches to diagnosis and …

Artificial intelligence (AI) has demonstrated promise in predicting acute kidney injury (AKI),
however, clinical adoption of these models requires interpretability and transportability. Non …

Importance Acute kidney injury (AKI) is a heterogeneous syndrome prevalent among
hospitalized patients. Personalized risk estimation and risk factor identification may allow …

Acute kidney injury (AKI), which is a common complication of acute illnesses, affects the
health of individuals in community, acute care and post-acute care settings. Although the …

Rationale & Objective Risk prediction tools for assisting acute kidney injury (AKI)
management have focused on AKI onset but have infrequently addressed kidney recovery …

Background The number of studies applying machine learning (ML) to predict acute kidney
injury (AKI) has grown steadily over the past decade. We assess and critically appraise the …

With the wider availability of healthcare data such as Electronic Health Records (EHR), more
and more data-driven based approaches have been proposed to improve the quality-of-care …

Objectives The aim of this study was to develop a machine learning (ML)–based risk
stratification tool for 1-year mortality in transcatheter mitral valve repair (TMVR) patients …

Acute kidney injury (AKI) is a serious clinical comorbidity with clear short-term and long-term
prognostic implications for inpatients. The diversity of risk factors for AKI has been …