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A Review of the Clinical Applications of Artificial Intelligence in Abdominal Imaging
Artificial intelligence (AI) has been a topic of substantial interest for radiologists in recent years. Although many of the first clinical applications were in the neuro, cardiothoracic, and breast imaging subspecialties, the number of investigated and real-world applications of body imaging has be...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10529018/ https://www.ncbi.nlm.nih.gov/pubmed/37761253 http://dx.doi.org/10.3390/diagnostics13182889 |
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author | Mervak, Benjamin M. Fried, Jessica G. Wasnik, Ashish P. |
author_facet | Mervak, Benjamin M. Fried, Jessica G. Wasnik, Ashish P. |
author_sort | Mervak, Benjamin M. |
collection | PubMed |
description | Artificial intelligence (AI) has been a topic of substantial interest for radiologists in recent years. Although many of the first clinical applications were in the neuro, cardiothoracic, and breast imaging subspecialties, the number of investigated and real-world applications of body imaging has been increasing, with more than 30 FDA-approved algorithms now available for applications in the abdomen and pelvis. In this manuscript, we explore some of the fundamentals of artificial intelligence and machine learning, review major functions that AI algorithms may perform, introduce current and potential future applications of AI in abdominal imaging, provide a basic understanding of the pathways by which AI algorithms can receive FDA approval, and explore some of the challenges with the implementation of AI in clinical practice. |
format | Online Article Text |
id | pubmed-10529018 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-105290182023-09-28 A Review of the Clinical Applications of Artificial Intelligence in Abdominal Imaging Mervak, Benjamin M. Fried, Jessica G. Wasnik, Ashish P. Diagnostics (Basel) Review Artificial intelligence (AI) has been a topic of substantial interest for radiologists in recent years. Although many of the first clinical applications were in the neuro, cardiothoracic, and breast imaging subspecialties, the number of investigated and real-world applications of body imaging has been increasing, with more than 30 FDA-approved algorithms now available for applications in the abdomen and pelvis. In this manuscript, we explore some of the fundamentals of artificial intelligence and machine learning, review major functions that AI algorithms may perform, introduce current and potential future applications of AI in abdominal imaging, provide a basic understanding of the pathways by which AI algorithms can receive FDA approval, and explore some of the challenges with the implementation of AI in clinical practice. MDPI 2023-09-08 /pmc/articles/PMC10529018/ /pubmed/37761253 http://dx.doi.org/10.3390/diagnostics13182889 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Mervak, Benjamin M. Fried, Jessica G. Wasnik, Ashish P. A Review of the Clinical Applications of Artificial Intelligence in Abdominal Imaging |
title | A Review of the Clinical Applications of Artificial Intelligence in Abdominal Imaging |
title_full | A Review of the Clinical Applications of Artificial Intelligence in Abdominal Imaging |
title_fullStr | A Review of the Clinical Applications of Artificial Intelligence in Abdominal Imaging |
title_full_unstemmed | A Review of the Clinical Applications of Artificial Intelligence in Abdominal Imaging |
title_short | A Review of the Clinical Applications of Artificial Intelligence in Abdominal Imaging |
title_sort | review of the clinical applications of artificial intelligence in abdominal imaging |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10529018/ https://www.ncbi.nlm.nih.gov/pubmed/37761253 http://dx.doi.org/10.3390/diagnostics13182889 |
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