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Artificial intelligence for advanced analysis of coronary plaque
The field of coronary plaque analysis is advancing including more quantitative analysis of coronary artery diseases such as plaque burden, high-risk plaque features, computed tomography-derived fractional flow reserve, and radiomics. Although these biomarkers have shown great promise for the diagnos...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10132604/ https://www.ncbi.nlm.nih.gov/pubmed/37125298 http://dx.doi.org/10.1093/eurheartjsupp/suad038 |
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author | van Assen, Marly von Knebel Doeberitz, Philipp Quyyumi, Arshed A De Cecco, Carlo N |
author_facet | van Assen, Marly von Knebel Doeberitz, Philipp Quyyumi, Arshed A De Cecco, Carlo N |
author_sort | van Assen, Marly |
collection | PubMed |
description | The field of coronary plaque analysis is advancing including more quantitative analysis of coronary artery diseases such as plaque burden, high-risk plaque features, computed tomography-derived fractional flow reserve, and radiomics. Although these biomarkers have shown great promise for the diagnosis and prognosis of cardiac patients in a research setting, many of these advanced analyses are labour and time intensive and therefore hard to implement in daily clinical practice. Artificial intelligence (AI) is playing an increasing role in supporting the quantification of these new biomarkers. AI offers the opportunity to increase efficiency, reduce human error and reader variability and to increase the accuracy of diagnosis and prognosis by automating many processing and supporting clinicians in their decision-making. With the use of AI these novel analysis approaches for coronary artery disease can be made feasible for clinical practice without increasing cost and workload and potentially improve patient care. |
format | Online Article Text |
id | pubmed-10132604 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-101326042023-04-27 Artificial intelligence for advanced analysis of coronary plaque van Assen, Marly von Knebel Doeberitz, Philipp Quyyumi, Arshed A De Cecco, Carlo N Eur Heart J Suppl PLACE 2022 Supplement Paper The field of coronary plaque analysis is advancing including more quantitative analysis of coronary artery diseases such as plaque burden, high-risk plaque features, computed tomography-derived fractional flow reserve, and radiomics. Although these biomarkers have shown great promise for the diagnosis and prognosis of cardiac patients in a research setting, many of these advanced analyses are labour and time intensive and therefore hard to implement in daily clinical practice. Artificial intelligence (AI) is playing an increasing role in supporting the quantification of these new biomarkers. AI offers the opportunity to increase efficiency, reduce human error and reader variability and to increase the accuracy of diagnosis and prognosis by automating many processing and supporting clinicians in their decision-making. With the use of AI these novel analysis approaches for coronary artery disease can be made feasible for clinical practice without increasing cost and workload and potentially improve patient care. Oxford University Press 2023-04-26 /pmc/articles/PMC10132604/ /pubmed/37125298 http://dx.doi.org/10.1093/eurheartjsupp/suad038 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of the European Society of Cardiology. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | PLACE 2022 Supplement Paper van Assen, Marly von Knebel Doeberitz, Philipp Quyyumi, Arshed A De Cecco, Carlo N Artificial intelligence for advanced analysis of coronary plaque |
title | Artificial intelligence for advanced analysis of coronary plaque |
title_full | Artificial intelligence for advanced analysis of coronary plaque |
title_fullStr | Artificial intelligence for advanced analysis of coronary plaque |
title_full_unstemmed | Artificial intelligence for advanced analysis of coronary plaque |
title_short | Artificial intelligence for advanced analysis of coronary plaque |
title_sort | artificial intelligence for advanced analysis of coronary plaque |
topic | PLACE 2022 Supplement Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10132604/ https://www.ncbi.nlm.nih.gov/pubmed/37125298 http://dx.doi.org/10.1093/eurheartjsupp/suad038 |
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