[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 …

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 …

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 …

Prediction of acute kidney injury with a machine learning algorithm using electronic health record data

H Mohamadlou, A Lynn-Palevsky… - Canadian journal of …, 2018 - journals.sagepub.com
Background: A major problem in treating acute kidney injury (AKI) is that clinical criteria for
recognition are markers of established kidney damage or impaired function; treatment …

A simpler machine learning model for acute kidney injury risk stratification in hospitalized patients

Y Hu, K Liu, K Ho, D Riviello, J Brown… - Journal of Clinical …, 2022 - mdpi.com
Background: Hospitalization-associated acute kidney injury (AKI), affecting one-in-five
inpatients, is associated with increased mortality and major adverse cardiac/kidney …

Artificial intelligence in acute kidney injury risk prediction

J Gameiro, T Branco, JA Lopes - Journal of clinical medicine, 2020 - mdpi.com
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 …

Does artificial intelligence make clinical decision better? A review of artificial intelligence and machine learning in acute kidney injury prediction

TH Lee, JJ Chen, CT Cheng, CH Chang - Healthcare, 2021 - mdpi.com
Acute kidney injury (AKI) is a common complication of hospitalization that greatly and
negatively affects the short-term and long-term outcomes of patients. Current guidelines use …

A continual prediction model for inpatient acute kidney injury

RJ Kate, N Pearce, D Mazumdar… - Computers in biology and …, 2020 - Elsevier
Acute kidney injury (AKI) commonly occurs in hospitalized patients and can lead to serious
medical complications. But it is preventable and potentially reversible with early diagnosis …

Prediction and detection models for acute kidney injury in hospitalized older adults

RJ Kate, RM Perez, D Mazumdar… - BMC medical informatics …, 2016 - Springer
Abstract Background Acute Kidney Injury (AKI) occurs in at least 5% of hospitalized patients
and can result in 40–70% morbidity and mortality. Even following recovery, many subjects …

External validation of a commercial acute kidney injury predictive model

S Dutta, DS McEvoy, LN Dunham, R Stevens, D Rubins… - NEJM AI, 2024 - ai.nejm.org
Background Hospital-acquired acute kidney injury (HA-AKI), a common complication in
hospitalized patients that increases morbidity and mortality, is challenging to predict given its …