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The Artificial Intelligence in Digital Radiology: Part 1: The Challenges, Acceptance and Consensus
Artificial intelligence is having important developments in the world of digital radiology also thanks to the boost given to the research sector by the COVID-19 pandemic. In the last two years, there was an important development of studies focused on both challenges and acceptance and consensus in t...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8949694/ https://www.ncbi.nlm.nih.gov/pubmed/35326987 http://dx.doi.org/10.3390/healthcare10030509 |
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author | Giansanti, Daniele Di Basilio, Francesco |
author_facet | Giansanti, Daniele Di Basilio, Francesco |
author_sort | Giansanti, Daniele |
collection | PubMed |
description | Artificial intelligence is having important developments in the world of digital radiology also thanks to the boost given to the research sector by the COVID-19 pandemic. In the last two years, there was an important development of studies focused on both challenges and acceptance and consensus in the field of Artificial Intelligence. The challenges and acceptance and consensus are two strategic aspects in the development and integration of technologies in the health domain. The study conducted two narrative reviews by means of two parallel points of view to take stock both on the ongoing challenges and on initiatives conducted to face the acceptance and consensus in this area. The methodology of the review was based on: (I) search of PubMed and Scopus and (II) an eligibility assessment, using parameters with 5 levels of score. The results have: (a) highlighted and categorized the important challenges in place. (b) Illustrated the different types of studies conducted through original questionnaires. The study suggests for future research based on questionnaires a better calibration and inclusion of the challenges in place together with validation and administration paths at an international level. |
format | Online Article Text |
id | pubmed-8949694 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-89496942022-03-26 The Artificial Intelligence in Digital Radiology: Part 1: The Challenges, Acceptance and Consensus Giansanti, Daniele Di Basilio, Francesco Healthcare (Basel) Review Artificial intelligence is having important developments in the world of digital radiology also thanks to the boost given to the research sector by the COVID-19 pandemic. In the last two years, there was an important development of studies focused on both challenges and acceptance and consensus in the field of Artificial Intelligence. The challenges and acceptance and consensus are two strategic aspects in the development and integration of technologies in the health domain. The study conducted two narrative reviews by means of two parallel points of view to take stock both on the ongoing challenges and on initiatives conducted to face the acceptance and consensus in this area. The methodology of the review was based on: (I) search of PubMed and Scopus and (II) an eligibility assessment, using parameters with 5 levels of score. The results have: (a) highlighted and categorized the important challenges in place. (b) Illustrated the different types of studies conducted through original questionnaires. The study suggests for future research based on questionnaires a better calibration and inclusion of the challenges in place together with validation and administration paths at an international level. MDPI 2022-03-10 /pmc/articles/PMC8949694/ /pubmed/35326987 http://dx.doi.org/10.3390/healthcare10030509 Text en © 2022 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 Giansanti, Daniele Di Basilio, Francesco The Artificial Intelligence in Digital Radiology: Part 1: The Challenges, Acceptance and Consensus |
title | The Artificial Intelligence in Digital Radiology: Part 1: The Challenges, Acceptance and Consensus |
title_full | The Artificial Intelligence in Digital Radiology: Part 1: The Challenges, Acceptance and Consensus |
title_fullStr | The Artificial Intelligence in Digital Radiology: Part 1: The Challenges, Acceptance and Consensus |
title_full_unstemmed | The Artificial Intelligence in Digital Radiology: Part 1: The Challenges, Acceptance and Consensus |
title_short | The Artificial Intelligence in Digital Radiology: Part 1: The Challenges, Acceptance and Consensus |
title_sort | artificial intelligence in digital radiology: part 1: the challenges, acceptance and consensus |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8949694/ https://www.ncbi.nlm.nih.gov/pubmed/35326987 http://dx.doi.org/10.3390/healthcare10030509 |
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