Artificial intelligence and machine learning in cardiovascular computed tomography

Computed tomography (CT) is emerging as a prominent diagnostic modality in the field of cardiovascular imaging. Artificial intelligence (AI) is making significant strides in the field of information technology, the commercial industry, and health care. Machine learning (ML), a branch of AI, can opti...

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Autores principales: Seetharam, Karthik, Bhat, Premila, Orris, Maxine, Prabhu, Hejmadi, Shah, Jilan, Asti, Deepak, Chawla, Preety, Mir, Tanveer
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Baishideng Publishing Group Inc 2021
Materias:
Minireviews
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8554359/
https://www.ncbi.nlm.nih.gov/pubmed/34754399
http://dx.doi.org/10.4330/wjc.v13.i10.546
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author Seetharam, Karthik
Bhat, Premila
Orris, Maxine
Prabhu, Hejmadi
Shah, Jilan
Asti, Deepak
Chawla, Preety
Mir, Tanveer
author_facet Seetharam, Karthik
Bhat, Premila
Orris, Maxine
Prabhu, Hejmadi
Shah, Jilan
Asti, Deepak
Chawla, Preety
Mir, Tanveer
author_sort Seetharam, Karthik
collection PubMed
description Computed tomography (CT) is emerging as a prominent diagnostic modality in the field of cardiovascular imaging. Artificial intelligence (AI) is making significant strides in the field of information technology, the commercial industry, and health care. Machine learning (ML), a branch of AI, can optimize the performance of CT and augment the assessment of coronary artery disease. These ML platforms can automate multiple tasks, perform calculations, and integrate information from a variety of data sources. In this review article, we explore the ML in CT imaging.
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spelling pubmed-85543592021-11-08 Artificial intelligence and machine learning in cardiovascular computed tomography Seetharam, Karthik Bhat, Premila Orris, Maxine Prabhu, Hejmadi Shah, Jilan Asti, Deepak Chawla, Preety Mir, Tanveer World J Cardiol Minireviews Computed tomography (CT) is emerging as a prominent diagnostic modality in the field of cardiovascular imaging. Artificial intelligence (AI) is making significant strides in the field of information technology, the commercial industry, and health care. Machine learning (ML), a branch of AI, can optimize the performance of CT and augment the assessment of coronary artery disease. These ML platforms can automate multiple tasks, perform calculations, and integrate information from a variety of data sources. In this review article, we explore the ML in CT imaging. Baishideng Publishing Group Inc 2021-10-26 2021-10-26 /pmc/articles/PMC8554359/ /pubmed/34754399 http://dx.doi.org/10.4330/wjc.v13.i10.546 Text en ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved. https://creativecommons.org/licenses/by-nc/4.0/This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
spellingShingle Minireviews
Seetharam, Karthik
Bhat, Premila
Orris, Maxine
Prabhu, Hejmadi
Shah, Jilan
Asti, Deepak
Chawla, Preety
Mir, Tanveer
Artificial intelligence and machine learning in cardiovascular computed tomography
title Artificial intelligence and machine learning in cardiovascular computed tomography
title_full Artificial intelligence and machine learning in cardiovascular computed tomography
title_fullStr Artificial intelligence and machine learning in cardiovascular computed tomography
title_full_unstemmed Artificial intelligence and machine learning in cardiovascular computed tomography
title_short Artificial intelligence and machine learning in cardiovascular computed tomography
title_sort artificial intelligence and machine learning in cardiovascular computed tomography
topic Minireviews
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8554359/
https://www.ncbi.nlm.nih.gov/pubmed/34754399
http://dx.doi.org/10.4330/wjc.v13.i10.546
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