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Artificial intelligence in the pediatric echocardiography laboratory: Automation, physiology, and outcomes

Artificial intelligence (AI) is frequently used in non-medical fields to assist with automation and decision-making. The potential for AI in pediatric cardiology, especially in the echocardiography laboratory, is very high. There are multiple tasks AI is designed to do that could improve the quality...

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Autores principales: Nguyen, Minh B., Villemain, Olivier, Friedberg, Mark K., Lovstakken, Lasse, Rusin, Craig G., Mertens, Luc
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10365116/
https://www.ncbi.nlm.nih.gov/pubmed/37492680
http://dx.doi.org/10.3389/fradi.2022.881777
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author Nguyen, Minh B.
Villemain, Olivier
Friedberg, Mark K.
Lovstakken, Lasse
Rusin, Craig G.
Mertens, Luc
author_facet Nguyen, Minh B.
Villemain, Olivier
Friedberg, Mark K.
Lovstakken, Lasse
Rusin, Craig G.
Mertens, Luc
author_sort Nguyen, Minh B.
collection PubMed
description Artificial intelligence (AI) is frequently used in non-medical fields to assist with automation and decision-making. The potential for AI in pediatric cardiology, especially in the echocardiography laboratory, is very high. There are multiple tasks AI is designed to do that could improve the quality, interpretation, and clinical application of echocardiographic data at the level of the sonographer, echocardiographer, and clinician. In this state-of-the-art review, we highlight the pertinent literature on machine learning in echocardiography and discuss its applications in the pediatric echocardiography lab with a focus on automation of the pediatric echocardiogram and the use of echo data to better understand physiology and outcomes in pediatric cardiology. We also discuss next steps in utilizing AI in pediatric echocardiography.
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spelling pubmed-103651162023-07-25 Artificial intelligence in the pediatric echocardiography laboratory: Automation, physiology, and outcomes Nguyen, Minh B. Villemain, Olivier Friedberg, Mark K. Lovstakken, Lasse Rusin, Craig G. Mertens, Luc Front Radiol Radiology Artificial intelligence (AI) is frequently used in non-medical fields to assist with automation and decision-making. The potential for AI in pediatric cardiology, especially in the echocardiography laboratory, is very high. There are multiple tasks AI is designed to do that could improve the quality, interpretation, and clinical application of echocardiographic data at the level of the sonographer, echocardiographer, and clinician. In this state-of-the-art review, we highlight the pertinent literature on machine learning in echocardiography and discuss its applications in the pediatric echocardiography lab with a focus on automation of the pediatric echocardiogram and the use of echo data to better understand physiology and outcomes in pediatric cardiology. We also discuss next steps in utilizing AI in pediatric echocardiography. Frontiers Media S.A. 2022-09-09 /pmc/articles/PMC10365116/ /pubmed/37492680 http://dx.doi.org/10.3389/fradi.2022.881777 Text en Copyright © 2022 Nguyen, Villemain, Friedberg, Lovstakken, Rusin and Mertens. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Radiology
Nguyen, Minh B.
Villemain, Olivier
Friedberg, Mark K.
Lovstakken, Lasse
Rusin, Craig G.
Mertens, Luc
Artificial intelligence in the pediatric echocardiography laboratory: Automation, physiology, and outcomes
title Artificial intelligence in the pediatric echocardiography laboratory: Automation, physiology, and outcomes
title_full Artificial intelligence in the pediatric echocardiography laboratory: Automation, physiology, and outcomes
title_fullStr Artificial intelligence in the pediatric echocardiography laboratory: Automation, physiology, and outcomes
title_full_unstemmed Artificial intelligence in the pediatric echocardiography laboratory: Automation, physiology, and outcomes
title_short Artificial intelligence in the pediatric echocardiography laboratory: Automation, physiology, and outcomes
title_sort artificial intelligence in the pediatric echocardiography laboratory: automation, physiology, and outcomes
topic Radiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10365116/
https://www.ncbi.nlm.nih.gov/pubmed/37492680
http://dx.doi.org/10.3389/fradi.2022.881777
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