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Artificial intelligence and machine learning in spine research

Artificial intelligence (AI) and machine learning (ML) techniques are revolutionizing several industrial and research fields like computer vision, autonomous driving, natural language processing, and speech recognition. These novel tools are already having a major impact in radiology, diagnostics, a...

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Detalles Bibliográficos
Autores principales: Galbusera, Fabio, Casaroli, Gloria, Bassani, Tito
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6686793/
https://www.ncbi.nlm.nih.gov/pubmed/31463458
http://dx.doi.org/10.1002/jsp2.1044
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author Galbusera, Fabio
Casaroli, Gloria
Bassani, Tito
author_facet Galbusera, Fabio
Casaroli, Gloria
Bassani, Tito
author_sort Galbusera, Fabio
collection PubMed
description Artificial intelligence (AI) and machine learning (ML) techniques are revolutionizing several industrial and research fields like computer vision, autonomous driving, natural language processing, and speech recognition. These novel tools are already having a major impact in radiology, diagnostics, and many other fields in which the availability of automated solution may benefit the accuracy and repeatability of the execution of critical tasks. In this narrative review, we first present a brief description of the various techniques that are being developed nowadays, with special focus on those used in spine research. Then, we describe the applications of AI and ML to problems related to the spine which have been published so far, including the localization of vertebrae and discs in radiological images, image segmentation, computer‐aided diagnosis, prediction of clinical outcomes and complications, decision support systems, content‐based image retrieval, biomechanics, and motion analysis. Finally, we briefly discuss major ethical issues related to the use of AI in healthcare, namely, accountability, risk of biased decisions as well as data privacy and security, which are nowadays being debated in the scientific community and by regulatory agencies.
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spelling pubmed-66867932019-08-28 Artificial intelligence and machine learning in spine research Galbusera, Fabio Casaroli, Gloria Bassani, Tito JOR Spine Reviews Artificial intelligence (AI) and machine learning (ML) techniques are revolutionizing several industrial and research fields like computer vision, autonomous driving, natural language processing, and speech recognition. These novel tools are already having a major impact in radiology, diagnostics, and many other fields in which the availability of automated solution may benefit the accuracy and repeatability of the execution of critical tasks. In this narrative review, we first present a brief description of the various techniques that are being developed nowadays, with special focus on those used in spine research. Then, we describe the applications of AI and ML to problems related to the spine which have been published so far, including the localization of vertebrae and discs in radiological images, image segmentation, computer‐aided diagnosis, prediction of clinical outcomes and complications, decision support systems, content‐based image retrieval, biomechanics, and motion analysis. Finally, we briefly discuss major ethical issues related to the use of AI in healthcare, namely, accountability, risk of biased decisions as well as data privacy and security, which are nowadays being debated in the scientific community and by regulatory agencies. John Wiley & Sons, Inc. 2019-03-05 /pmc/articles/PMC6686793/ /pubmed/31463458 http://dx.doi.org/10.1002/jsp2.1044 Text en © 2019 The Authors. JOR Spine published by Wiley Periodicals, Inc. on behalf of Orthopaedic Research Society This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Reviews
Galbusera, Fabio
Casaroli, Gloria
Bassani, Tito
Artificial intelligence and machine learning in spine research
title Artificial intelligence and machine learning in spine research
title_full Artificial intelligence and machine learning in spine research
title_fullStr Artificial intelligence and machine learning in spine research
title_full_unstemmed Artificial intelligence and machine learning in spine research
title_short Artificial intelligence and machine learning in spine research
title_sort artificial intelligence and machine learning in spine research
topic Reviews
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6686793/
https://www.ncbi.nlm.nih.gov/pubmed/31463458
http://dx.doi.org/10.1002/jsp2.1044
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