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Artificial Intelligence in Acute Kidney Injury Risk Prediction

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 identify patients at risk for AKI and to diagnose subclinical AKI in order to improve patient outcomes. The advances in clin...

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Detalles Bibliográficos
Autores principales: Gameiro, Joana, Branco, Tiago, Lopes, José António
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7141311/
https://www.ncbi.nlm.nih.gov/pubmed/32138284
http://dx.doi.org/10.3390/jcm9030678
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author Gameiro, Joana
Branco, Tiago
Lopes, José António
author_facet Gameiro, Joana
Branco, Tiago
Lopes, José António
author_sort Gameiro, Joana
collection PubMed
description 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 identify patients at risk for AKI and to diagnose subclinical AKI in order to improve patient outcomes. The advances in clinical informatics and the increasing availability of electronic medical records have allowed for the development of artificial intelligence predictive models of risk estimation in AKI. In this review, we discussed the progress of AKI risk prediction from risk scores to electronic alerts to machine learning methods.
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spelling pubmed-71413112020-04-10 Artificial Intelligence in Acute Kidney Injury Risk Prediction Gameiro, Joana Branco, Tiago Lopes, José António J Clin Med Review 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 identify patients at risk for AKI and to diagnose subclinical AKI in order to improve patient outcomes. The advances in clinical informatics and the increasing availability of electronic medical records have allowed for the development of artificial intelligence predictive models of risk estimation in AKI. In this review, we discussed the progress of AKI risk prediction from risk scores to electronic alerts to machine learning methods. MDPI 2020-03-03 /pmc/articles/PMC7141311/ /pubmed/32138284 http://dx.doi.org/10.3390/jcm9030678 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Gameiro, Joana
Branco, Tiago
Lopes, José António
Artificial Intelligence in Acute Kidney Injury Risk Prediction
title Artificial Intelligence in Acute Kidney Injury Risk Prediction
title_full Artificial Intelligence in Acute Kidney Injury Risk Prediction
title_fullStr Artificial Intelligence in Acute Kidney Injury Risk Prediction
title_full_unstemmed Artificial Intelligence in Acute Kidney Injury Risk Prediction
title_short Artificial Intelligence in Acute Kidney Injury Risk Prediction
title_sort artificial intelligence in acute kidney injury risk prediction
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7141311/
https://www.ncbi.nlm.nih.gov/pubmed/32138284
http://dx.doi.org/10.3390/jcm9030678
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