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 …

[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 …

The development of a machine learning inpatient acute kidney injury prediction model

JL Koyner, KA Carey, DP Edelson… - Critical care …, 2018 - journals.lww.com
Objectives: To develop an acute kidney injury risk prediction model using electronic health
record data for longitudinal use in hospitalized patients. Design: Observational cohort study …

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 …

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 …

Internal and external validation of a machine learning risk score for acute kidney injury

MM Churpek, KA Carey, DP Edelson, T Singh… - JAMA network …, 2020 - jamanetwork.com
Importance Acute kidney injury (AKI) is associated with increased morbidity and mortality in
hospitalized patients. Current methods to identify patients at high risk of AKI are limited, and …

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 …

Automated continuous acute kidney injury prediction and surveillance: a random forest model

C Chiofolo, N Chbat, E Ghosh, L Eshelman… - Mayo Clinic …, 2019 - Elsevier
Objective To develop and validate a prediction model of acute kidney injury (AKI) of any
severity that could be used for AKI surveillance and management to improve clinical …

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 …

Predicting acute kidney injury in critically ill patients using comorbid conditions utilizing machine learning

K Shawwa, E Ghosh, S Lanius, E Schwager… - Clinical Kidney …, 2021 - academic.oup.com
Background Acute kidney injury (AKI) carries a poor prognosis. Its incidence is increasing in
the intensive care unit (ICU). Our purpose in this study is to develop and externally validate a …