An empirical study on KDIGO-defined acute kidney injury prediction in the intensive care unit

X Lyu, B Fan, M Hüser, P Hartout, T Gumbsch… - …, 2024 - academic.oup.com
Motivation Acute kidney injury (AKI) is a syndrome that affects a large fraction of all critically
ill patients, and early diagnosis to receive adequate treatment is as imperative as it is …

Continuous and early prediction of future moderate and severe Acute Kidney Injury in critically ill patients: development and multi-centric, multi-national external …

F Alfieri, A Ancona, G Tripepi, A Rubeis, N Arjoldi… - PLoS …, 2023 - journals.plos.org
Background Acute Kidney Injury (AKI) is a major complication in patients admitted to
Intensive Care Units (ICU), causing both clinical and economic burden on the healthcare …

[HTML][HTML] A prediction and interpretation framework of acute kidney injury in critical care

K Gong, HK Lee, K Yu, X Xie, J Li - Journal of Biomedical Informatics, 2021 - Elsevier
Acute kidney injury (AKI) is a common clinical condition with high mortality and resource
consumption. Early identification of high-risk patients to achieve an appropriate allocation of …

[HTML][HTML] Convolutional neural network model for intensive care unit acute kidney injury prediction

S Le, A Allen, J Calvert, PM Palevsky, G Braden… - Kidney international …, 2021 - Elsevier
Introduction Acute kidney injury (AKI) is common among hospitalized patients and has a
significant impact on morbidity and mortality. Although early prediction of AKI has the …

Machine learning clinical prediction models for acute kidney injury: the impact of baseline creatinine on prediction efficacy

A Kamel Rahimi, M Ghadimi, AH van der Vegt… - BMC Medical Informatics …, 2023 - Springer
Abstract Background There are many Machine Learning (ML) models which predict acute
kidney injury (AKI) for hospitalised patients. While a primary goal of these models is to …

Prediction of acute kidney injury in ICU with gradient boosting decision tree algorithms

W Gao, J Wang, L Zhou, Q Luo, Y Lao, H Lyu… - Computers in biology and …, 2022 - Elsevier
Purpose To predict acute kidney injury (AKI) in a large intensive care unit (ICU) database.
Materials and methods A total of 30,020 ICU admissions with 17,222 AKI episodes were …

Development and validation of a deep interpretable network for continuous acute kidney injury prediction in critically ill patients

M Yang, S Liu, T Hao, C Ma, H Chen, Y Li, C Wu… - Artificial Intelligence in …, 2024 - Elsevier
Early detection of acute kidney injury (AKI) may provide a crucial window of opportunity to
prevent further injury, which helps improve clinical outcomes. This study aimed to develop a …

Acute kidney injury prediction with gradient boosting decision trees enriched with temporal features

S Golovco, M Mantovani, C Combi… - 2022 IEEE 10th …, 2022 - ieeexplore.ieee.org
This paper aims to predict the risk of Acute Kidney Injury (AKI) in intensive care units (ICUs)
using machine learning techniques and statistical approaches. The data used in the study …

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 …

Accurate and interpretable prediction of ICU-acquired AKI

E Schwager, E Ghosh, L Eshelman, KS Pasupathy… - Journal of Critical …, 2023 - Elsevier
Purpose We developed and validated two parsimonious algorithms to predict the time of
diagnosis of any stage of acute kidney injury (any-AKI) or moderate-to-severe AKI in …