Utilizing Electronic Health Records to Predict Acute Kidney Injury Risk and Outcomes: Workgroup Statements from the 15th ADQI Consensus Conference

SM Sutherland, LS Chawla… - Canadian journal of …, 2016 - journals.sagepub.com
The data contained within the electronic health record (EHR) is “big” from the standpoint of
volume, velocity, and variety. These circumstances and the pervasive trend towards EHR …

Acute kidney injury and big data

SM Sutherland, SL Goldstein… - Acute Kidney Injury-Basic …, 2018 - karger.com
The recognition of a standardized, consensus definition for acute kidney injury (AKI) has
been an important milestone in critical care nephrology, which has facilitated innovation in …

Multi-perspective predictive modeling for acute kidney injury in general hospital populations using electronic medical records

J He, Y Hu, X Zhang, L Wu, LR Waitman, M Liu - JAMIA open, 2019 - academic.oup.com
Objectives Acute kidney injury (AKI) in hospitalized patients puts them at much higher risk for
developing future health problems such as chronic kidney disease, stroke, and heart …

[HTML][HTML] A simple real-time model for predicting acute kidney injury in hospitalized patients in the US: a descriptive modeling study

M Simonov, U Ugwuowo, E Moreira, Y Yamamoto… - PLoS …, 2019 - journals.plos.org
Background Acute kidney injury (AKI) is an adverse event that carries significant morbidity.
Given that interventions after AKI occurrence have poor performance, there is substantial …

Optimizing Administrative Datasets to Examine Acute Kidney Injury in the Era of Big Data: Workgroup Statement from the 15th ADQI Consensus Conference

ED Siew, RK Basu, H Wunsch… - Canadian journal of …, 2016 - journals.sagepub.com
Purpose of review: The purpose of this review is to report how administrative data have been
used to study AKI, identify current limitations, and suggest how these data sources might be …

Acute kidney injury in real time: prediction, alerts, and clinical decision support

FP Wilson, JH Greenberg - Nephron, 2018 - karger.com
Broad adoption of electronic health record (EHR) systems has facilitated acute kidney injury
(AKI) research in 2 ways. First, the detection of AKI based on changes in serum creatinine …

Development and validation of a personalized model with transfer learning for acute kidney injury risk estimation using electronic health records

K Liu, X Zhang, W Chen, SL Alan, JA Kellum… - JAMA Network …, 2022 - jamanetwork.com
Importance Acute kidney injury (AKI) is a heterogeneous syndrome prevalent among
hospitalized patients. Personalized risk estimation and risk factor identification may allow …

[HTML][HTML] Predicting inpatient acute kidney injury over different time horizons: how early and accurate?

P Cheng, LR Waitman, Y Hu, M Liu - AMIA Annual Symposium …, 2017 - ncbi.nlm.nih.gov
Abstract Incidence of Acute Kidney Injury (AKI) has increased dramatically over the past two
decades due to rising prevalence of comorbidities and broadening repertoire of nephrotoxic …

Acute Kidney Injury in the Era of Big Data: The 15th Consensus Conference of the Acute Dialysis Quality Initiative (ADQI)

SM Bagshaw, SL Goldstein, C Ronco… - Canadian journal of …, 2016 - journals.sagepub.com
The world is immersed in “big data”. Big data has brought about radical innovations in the
methods used to capture, transfer, store and analyze the vast quantities of data generated …

Artificial intelligence to predict AKI: is it a breakthrough?

JA Kellum, A Bihorac - Nature Reviews Nephrology, 2019 - nature.com
Artificial intelligence to predict AKI: is it a breakthrough? | Nature Reviews Nephrology Skip to
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