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Artificial Intelligence in Musculoskeletal Oncological Radiology

BACKGROUND: Due to the rarity of primary bone tumors, precise radiologic diagnosis often requires an experienced musculoskeletal radiologist. In order to make the diagnosis more precise and to prevent the overlooking of potentially dangerous conditions, artificial intelligence has been continuously...

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Detalles Bibliográficos
Autores principales: Vogrin, Matjaz, Trojner, Teodor, Kelc, Robi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Sciendo 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7877260/
https://www.ncbi.nlm.nih.gov/pubmed/33885240
http://dx.doi.org/10.2478/raon-2020-0068
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author Vogrin, Matjaz
Trojner, Teodor
Kelc, Robi
author_facet Vogrin, Matjaz
Trojner, Teodor
Kelc, Robi
author_sort Vogrin, Matjaz
collection PubMed
description BACKGROUND: Due to the rarity of primary bone tumors, precise radiologic diagnosis often requires an experienced musculoskeletal radiologist. In order to make the diagnosis more precise and to prevent the overlooking of potentially dangerous conditions, artificial intelligence has been continuously incorporated into medical practice in recent decades. This paper reviews some of the most promising systems developed, including those for diagnosis of primary and secondary bone tumors, breast, lung and colon neoplasms. CONCLUSIONS: Although there is still a shortage of long-term studies confirming its benefits, there is probably a considerable potential for further development of computer-based expert systems aiming at a more efficient diagnosis of bone and soft tissue tumors.
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spelling pubmed-78772602021-03-01 Artificial Intelligence in Musculoskeletal Oncological Radiology Vogrin, Matjaz Trojner, Teodor Kelc, Robi Radiol Oncol Review BACKGROUND: Due to the rarity of primary bone tumors, precise radiologic diagnosis often requires an experienced musculoskeletal radiologist. In order to make the diagnosis more precise and to prevent the overlooking of potentially dangerous conditions, artificial intelligence has been continuously incorporated into medical practice in recent decades. This paper reviews some of the most promising systems developed, including those for diagnosis of primary and secondary bone tumors, breast, lung and colon neoplasms. CONCLUSIONS: Although there is still a shortage of long-term studies confirming its benefits, there is probably a considerable potential for further development of computer-based expert systems aiming at a more efficient diagnosis of bone and soft tissue tumors. Sciendo 2020-11-10 /pmc/articles/PMC7877260/ /pubmed/33885240 http://dx.doi.org/10.2478/raon-2020-0068 Text en © 2021 Matjaz Vogrin, Teodor Trojner, Robi Kelc, published by Sciendo http://creativecommons.org/licenses/by-nc-nd/3.0 This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.
spellingShingle Review
Vogrin, Matjaz
Trojner, Teodor
Kelc, Robi
Artificial Intelligence in Musculoskeletal Oncological Radiology
title Artificial Intelligence in Musculoskeletal Oncological Radiology
title_full Artificial Intelligence in Musculoskeletal Oncological Radiology
title_fullStr Artificial Intelligence in Musculoskeletal Oncological Radiology
title_full_unstemmed Artificial Intelligence in Musculoskeletal Oncological Radiology
title_short Artificial Intelligence in Musculoskeletal Oncological Radiology
title_sort artificial intelligence in musculoskeletal oncological radiology
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7877260/
https://www.ncbi.nlm.nih.gov/pubmed/33885240
http://dx.doi.org/10.2478/raon-2020-0068
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