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Steps to use artificial intelligence in echocardiography
Artificial intelligence (AI) has influenced every field of cardiovascular imaging in all phases from acquisition to reporting. Compared with computed tomography and magnetic resonance imaging, there is an issue of high observer variation in the interpretation of echocardiograms. Therefore, AI can he...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Singapore
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7549428/ https://www.ncbi.nlm.nih.gov/pubmed/33044715 http://dx.doi.org/10.1007/s12574-020-00496-4 |
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author | Kusunose, Kenya |
author_facet | Kusunose, Kenya |
author_sort | Kusunose, Kenya |
collection | PubMed |
description | Artificial intelligence (AI) has influenced every field of cardiovascular imaging in all phases from acquisition to reporting. Compared with computed tomography and magnetic resonance imaging, there is an issue of high observer variation in the interpretation of echocardiograms. Therefore, AI can help minimize the observer variation and provide accurate diagnosis in the field of echocardiography. In this review, we summarize the necessity for automated diagnosis in the echocardiographic field, and discuss the results of AI application to echocardiography and future perspectives. Currently, there are two roles for AI in cardiovascular imaging. One is the automation of tasks performed by humans, such as image segmentation, measurement of cardiac structural and functional parameters. The other is the discovery of clinically important insights. Most reported applications were focused on the automation of tasks. Moreover, algorithms that can obtain cardiac measurements are also being reported. In the next stage, AI can be expected to expand and enrich existing knowledge. With the continual evolution of technology, cardiologists should become well versed in this new knowledge of AI and be able to harness it as a tool. AI can be incorporated into everyday clinical practice and become a valuable aid for many healthcare professionals dealing with cardiovascular diseases. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s12574-020-00496-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-7549428 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer Singapore |
record_format | MEDLINE/PubMed |
spelling | pubmed-75494282020-10-14 Steps to use artificial intelligence in echocardiography Kusunose, Kenya J Echocardiogr Review Article Artificial intelligence (AI) has influenced every field of cardiovascular imaging in all phases from acquisition to reporting. Compared with computed tomography and magnetic resonance imaging, there is an issue of high observer variation in the interpretation of echocardiograms. Therefore, AI can help minimize the observer variation and provide accurate diagnosis in the field of echocardiography. In this review, we summarize the necessity for automated diagnosis in the echocardiographic field, and discuss the results of AI application to echocardiography and future perspectives. Currently, there are two roles for AI in cardiovascular imaging. One is the automation of tasks performed by humans, such as image segmentation, measurement of cardiac structural and functional parameters. The other is the discovery of clinically important insights. Most reported applications were focused on the automation of tasks. Moreover, algorithms that can obtain cardiac measurements are also being reported. In the next stage, AI can be expected to expand and enrich existing knowledge. With the continual evolution of technology, cardiologists should become well versed in this new knowledge of AI and be able to harness it as a tool. AI can be incorporated into everyday clinical practice and become a valuable aid for many healthcare professionals dealing with cardiovascular diseases. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s12574-020-00496-4) contains supplementary material, which is available to authorized users. Springer Singapore 2020-10-12 2021 /pmc/articles/PMC7549428/ /pubmed/33044715 http://dx.doi.org/10.1007/s12574-020-00496-4 Text en © Japanese Society of Echocardiography 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Review Article Kusunose, Kenya Steps to use artificial intelligence in echocardiography |
title | Steps to use artificial intelligence in echocardiography |
title_full | Steps to use artificial intelligence in echocardiography |
title_fullStr | Steps to use artificial intelligence in echocardiography |
title_full_unstemmed | Steps to use artificial intelligence in echocardiography |
title_short | Steps to use artificial intelligence in echocardiography |
title_sort | steps to use artificial intelligence in echocardiography |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7549428/ https://www.ncbi.nlm.nih.gov/pubmed/33044715 http://dx.doi.org/10.1007/s12574-020-00496-4 |
work_keys_str_mv | AT kusunosekenya stepstouseartificialintelligenceinechocardiography |