Predicting Acute Kidney Injury: A Machine Learning Approach Using Electronic Health Records

SS Abdullah, N Rostamzadeh, K Sedig, AX Garg… - Information, 2020 - mdpi.com
Acute kidney injury (AKI) is a common complication in hospitalized patients and can result in
increased hospital stay, health-related costs, mortality and morbidity. A number of recent …

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 …

A machine learning model for acute kidney injury prediction with novel kidney biomarkers

S Narayan - 2022 Second International Conference on Next …, 2022 - ieeexplore.ieee.org
Background: AKI is a serious complication characterized by poor short-and long-term
outcomes in the intensive care unit. An increase in serum creatinine leads to impairment 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 …

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 …

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 …

Development of a knowledge mining approach to uncover heterogeneous risk predictors of acute kidney injury across age groups

L Wu, Y Hu, X Zhang, J Zhang, M Liu - International journal of medical …, 2022 - Elsevier
Objectives Acute kidney injury (AKI) risk increases with age and the underlying clinical
predictors may be heterogeneous across age strata. This study aims to uncover the AKI risk …

Systematic review of externally validated machine learning models for predicting acute kidney injury in general hospital patients

M Wainstein, E Flanagan, DW Johnson… - Frontiers in …, 2023 - frontiersin.org
Acute kidney injury (AKI) is one of the most common and consequential complications
among hospitalized patients. Timely AKI risk prediction may allow simple interventions that …

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 …