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Current and emerging artificial intelligence applications in chest imaging: a pediatric perspective
Artificial intelligence (AI) applications for chest radiography and chest CT are among the most developed applications in radiology. More than 40 certified AI products are available for chest radiography or chest CT. These AI products cover a wide range of abnormalities, including pneumonia, pneumot...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8409695/ https://www.ncbi.nlm.nih.gov/pubmed/34471961 http://dx.doi.org/10.1007/s00247-021-05146-0 |
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author | Schalekamp, Steven Klein, Willemijn M. van Leeuwen, Kicky G. |
author_facet | Schalekamp, Steven Klein, Willemijn M. van Leeuwen, Kicky G. |
author_sort | Schalekamp, Steven |
collection | PubMed |
description | Artificial intelligence (AI) applications for chest radiography and chest CT are among the most developed applications in radiology. More than 40 certified AI products are available for chest radiography or chest CT. These AI products cover a wide range of abnormalities, including pneumonia, pneumothorax and lung cancer. Most applications are aimed at detecting disease, complemented by products that characterize or quantify tissue. At present, none of the thoracic AI products is specifically designed for the pediatric population. However, some products developed to detect tuberculosis in adults are also applicable to children. Software is under development to detect early changes of cystic fibrosis on chest CT, which could be an interesting application for pediatric radiology. In this review, we give an overview of current AI products in thoracic radiology and cover recent literature about AI in chest radiography, with a focus on pediatric radiology. We also discuss possible pediatric applications. |
format | Online Article Text |
id | pubmed-8409695 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-84096952021-09-02 Current and emerging artificial intelligence applications in chest imaging: a pediatric perspective Schalekamp, Steven Klein, Willemijn M. van Leeuwen, Kicky G. Pediatr Radiol Artificial Intelligence in Pediatric Radiology Artificial intelligence (AI) applications for chest radiography and chest CT are among the most developed applications in radiology. More than 40 certified AI products are available for chest radiography or chest CT. These AI products cover a wide range of abnormalities, including pneumonia, pneumothorax and lung cancer. Most applications are aimed at detecting disease, complemented by products that characterize or quantify tissue. At present, none of the thoracic AI products is specifically designed for the pediatric population. However, some products developed to detect tuberculosis in adults are also applicable to children. Software is under development to detect early changes of cystic fibrosis on chest CT, which could be an interesting application for pediatric radiology. In this review, we give an overview of current AI products in thoracic radiology and cover recent literature about AI in chest radiography, with a focus on pediatric radiology. We also discuss possible pediatric applications. Springer Berlin Heidelberg 2021-09-01 2022 /pmc/articles/PMC8409695/ /pubmed/34471961 http://dx.doi.org/10.1007/s00247-021-05146-0 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This 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 | Artificial Intelligence in Pediatric Radiology Schalekamp, Steven Klein, Willemijn M. van Leeuwen, Kicky G. Current and emerging artificial intelligence applications in chest imaging: a pediatric perspective |
title | Current and emerging artificial intelligence applications in chest imaging: a pediatric perspective |
title_full | Current and emerging artificial intelligence applications in chest imaging: a pediatric perspective |
title_fullStr | Current and emerging artificial intelligence applications in chest imaging: a pediatric perspective |
title_full_unstemmed | Current and emerging artificial intelligence applications in chest imaging: a pediatric perspective |
title_short | Current and emerging artificial intelligence applications in chest imaging: a pediatric perspective |
title_sort | current and emerging artificial intelligence applications in chest imaging: a pediatric perspective |
topic | Artificial Intelligence in Pediatric Radiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8409695/ https://www.ncbi.nlm.nih.gov/pubmed/34471961 http://dx.doi.org/10.1007/s00247-021-05146-0 |
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