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The use of artificial intelligence in interventional cardiology

Artificial intelligence can be employed in many cardiological applications including image analysis, risk assessment, and patient monitoring. In the catheterization laboratory, it can act as a physician assistant, technician, or co-worker. First, by giving voice commands to the operator of the coron...

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Detalles Bibliográficos
Autores principales: Göçer, Hakan, Durukan, Ahmet Barış
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Bayçınar Medical Publishing 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10472472/
https://www.ncbi.nlm.nih.gov/pubmed/37664782
http://dx.doi.org/10.5606/tgkdc.dergisi.2023.24791
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author Göçer, Hakan
Durukan, Ahmet Barış
author_facet Göçer, Hakan
Durukan, Ahmet Barış
author_sort Göçer, Hakan
collection PubMed
description Artificial intelligence can be employed in many cardiological applications including image analysis, risk assessment, and patient monitoring. In the catheterization laboratory, it can act as a physician assistant, technician, or co-worker. First, by giving voice commands to the operator of the coronary angiography machine, it can ensure that the C-arm moves to the desired angle. It is able to make recommendations for stent size and type based on the analysis of angiography images which is also possible for peripheral and carotid interventions. For transcatheter aortic valve implantation, it can make recommendations for valve placement and size. Artificial intelligence-based image analysis algorithms can be used to support image analysis during catheter laboratory procedures. The challenges include the need for large, high-quality data sets and the development of accurate, reliable, and interpretable artificial intelligence algorithms.
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spelling pubmed-104724722023-09-02 The use of artificial intelligence in interventional cardiology Göçer, Hakan Durukan, Ahmet Barış Turk Gogus Kalp Damar Cerrahisi Derg Brief Report Artificial intelligence can be employed in many cardiological applications including image analysis, risk assessment, and patient monitoring. In the catheterization laboratory, it can act as a physician assistant, technician, or co-worker. First, by giving voice commands to the operator of the coronary angiography machine, it can ensure that the C-arm moves to the desired angle. It is able to make recommendations for stent size and type based on the analysis of angiography images which is also possible for peripheral and carotid interventions. For transcatheter aortic valve implantation, it can make recommendations for valve placement and size. Artificial intelligence-based image analysis algorithms can be used to support image analysis during catheter laboratory procedures. The challenges include the need for large, high-quality data sets and the development of accurate, reliable, and interpretable artificial intelligence algorithms. Bayçınar Medical Publishing 2023-07-27 /pmc/articles/PMC10472472/ /pubmed/37664782 http://dx.doi.org/10.5606/tgkdc.dergisi.2023.24791 Text en Copyright © 2023, Turkish Society of Cardiovascular Surgery https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Brief Report
Göçer, Hakan
Durukan, Ahmet Barış
The use of artificial intelligence in interventional cardiology
title The use of artificial intelligence in interventional cardiology
title_full The use of artificial intelligence in interventional cardiology
title_fullStr The use of artificial intelligence in interventional cardiology
title_full_unstemmed The use of artificial intelligence in interventional cardiology
title_short The use of artificial intelligence in interventional cardiology
title_sort use of artificial intelligence in interventional cardiology
topic Brief Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10472472/
https://www.ncbi.nlm.nih.gov/pubmed/37664782
http://dx.doi.org/10.5606/tgkdc.dergisi.2023.24791
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