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Prime Time for Artificial Intelligence in Interventional Radiology

Machine learning techniques, also known as artificial intelligence (AI), is about to dramatically change workflow and diagnostic capabilities in diagnostic radiology. The interest in AI in Interventional Radiology is rapidly gathering pace. With this early interest in AI in procedural medicine, IR c...

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Detalles Bibliográficos
Autores principales: Seah, Jarrel, Boeken, Tom, Sapoval, Marc, Goh, Gerard S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8921296/
https://www.ncbi.nlm.nih.gov/pubmed/35031822
http://dx.doi.org/10.1007/s00270-021-03044-4
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author Seah, Jarrel
Boeken, Tom
Sapoval, Marc
Goh, Gerard S.
author_facet Seah, Jarrel
Boeken, Tom
Sapoval, Marc
Goh, Gerard S.
author_sort Seah, Jarrel
collection PubMed
description Machine learning techniques, also known as artificial intelligence (AI), is about to dramatically change workflow and diagnostic capabilities in diagnostic radiology. The interest in AI in Interventional Radiology is rapidly gathering pace. With this early interest in AI in procedural medicine, IR could lead the way to AI research and clinical applications for all interventional medical fields. This review will address an overview of machine learning, radiomics and AI in the field of interventional radiology, enumerating the possible applications of such techniques, while also describing techniques to overcome the challenge of limited data when applying these techniques in interventional radiology. Lastly, this review will address common errors in research in this field and suggest pathways for those interested in learning and becoming involved about AI.
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spelling pubmed-89212962022-03-17 Prime Time for Artificial Intelligence in Interventional Radiology Seah, Jarrel Boeken, Tom Sapoval, Marc Goh, Gerard S. Cardiovasc Intervent Radiol Review Machine learning techniques, also known as artificial intelligence (AI), is about to dramatically change workflow and diagnostic capabilities in diagnostic radiology. The interest in AI in Interventional Radiology is rapidly gathering pace. With this early interest in AI in procedural medicine, IR could lead the way to AI research and clinical applications for all interventional medical fields. This review will address an overview of machine learning, radiomics and AI in the field of interventional radiology, enumerating the possible applications of such techniques, while also describing techniques to overcome the challenge of limited data when applying these techniques in interventional radiology. Lastly, this review will address common errors in research in this field and suggest pathways for those interested in learning and becoming involved about AI. Springer US 2022-01-14 2022 /pmc/articles/PMC8921296/ /pubmed/35031822 http://dx.doi.org/10.1007/s00270-021-03044-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Review
Seah, Jarrel
Boeken, Tom
Sapoval, Marc
Goh, Gerard S.
Prime Time for Artificial Intelligence in Interventional Radiology
title Prime Time for Artificial Intelligence in Interventional Radiology
title_full Prime Time for Artificial Intelligence in Interventional Radiology
title_fullStr Prime Time for Artificial Intelligence in Interventional Radiology
title_full_unstemmed Prime Time for Artificial Intelligence in Interventional Radiology
title_short Prime Time for Artificial Intelligence in Interventional Radiology
title_sort prime time for artificial intelligence in interventional radiology
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8921296/
https://www.ncbi.nlm.nih.gov/pubmed/35031822
http://dx.doi.org/10.1007/s00270-021-03044-4
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