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Evaluation of radiologist’s knowledge about the Artificial Intelligence in diagnostic radiology: a survey-based study
BACKGROUND: Advanced developments in diagnostic radiology have provided a rapid increase in the number of radiological investigations worldwide. Recently, Artificial Intelligence (AI) has been applied in diagnostic radiology. The purpose of developing such applications is to clinically validate and...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7412626/ https://www.ncbi.nlm.nih.gov/pubmed/32821436 http://dx.doi.org/10.1177/2058460120945320 |
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author | Tajaldeen, Abdulrahman Alghamdi, Salem |
author_facet | Tajaldeen, Abdulrahman Alghamdi, Salem |
author_sort | Tajaldeen, Abdulrahman |
collection | PubMed |
description | BACKGROUND: Advanced developments in diagnostic radiology have provided a rapid increase in the number of radiological investigations worldwide. Recently, Artificial Intelligence (AI) has been applied in diagnostic radiology. The purpose of developing such applications is to clinically validate and make them feasible for the current practice of diagnostic radiology, in which there is less time for diagnosis. PURPOSE: To assess radiologists’ knowledge about AI’s role and establish a baseline to help in providing educational activities on AI in diagnostic radiology in Saudi Arabia. MATERIAL AND METHODS: An online questionnaire was designed using QuestionPro software. The study was conducted in large hospitals located in different regions in Saudi Arabia. A total of 93 participants completed the questionnaire, of which 32 (34%) were trainee radiologists from year 1 to year 4 (R1–R4) of the residency programme, 33 (36%) were radiologists and fellows, and 28 (30%) were consultants. RESULTS: The responses to the question related to the use of AI on a daily basis illustrated that 76 (82%) of the participants were not using any AI software at all during daily interpretation of diagnostic images. Only 17 (18%) reported that they used AI software for diagnostic radiology. CONCLUSION: There is a significant lack of knowledge about AI in our residency programme and radiology departments at hospitals. Due to the rapid development of AI and its application in diagnostic radiology, there is an urgent need to enhance awareness about its role in different diagnostic fields. |
format | Online Article Text |
id | pubmed-7412626 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-74126262020-08-19 Evaluation of radiologist’s knowledge about the Artificial Intelligence in diagnostic radiology: a survey-based study Tajaldeen, Abdulrahman Alghamdi, Salem Acta Radiol Open Original Article BACKGROUND: Advanced developments in diagnostic radiology have provided a rapid increase in the number of radiological investigations worldwide. Recently, Artificial Intelligence (AI) has been applied in diagnostic radiology. The purpose of developing such applications is to clinically validate and make them feasible for the current practice of diagnostic radiology, in which there is less time for diagnosis. PURPOSE: To assess radiologists’ knowledge about AI’s role and establish a baseline to help in providing educational activities on AI in diagnostic radiology in Saudi Arabia. MATERIAL AND METHODS: An online questionnaire was designed using QuestionPro software. The study was conducted in large hospitals located in different regions in Saudi Arabia. A total of 93 participants completed the questionnaire, of which 32 (34%) were trainee radiologists from year 1 to year 4 (R1–R4) of the residency programme, 33 (36%) were radiologists and fellows, and 28 (30%) were consultants. RESULTS: The responses to the question related to the use of AI on a daily basis illustrated that 76 (82%) of the participants were not using any AI software at all during daily interpretation of diagnostic images. Only 17 (18%) reported that they used AI software for diagnostic radiology. CONCLUSION: There is a significant lack of knowledge about AI in our residency programme and radiology departments at hospitals. Due to the rapid development of AI and its application in diagnostic radiology, there is an urgent need to enhance awareness about its role in different diagnostic fields. SAGE Publications 2020-07-31 /pmc/articles/PMC7412626/ /pubmed/32821436 http://dx.doi.org/10.1177/2058460120945320 Text en © The Foundation Acta Radiologica 2020 https://creativecommons.org/licenses/by-nc/4.0/ Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Original Article Tajaldeen, Abdulrahman Alghamdi, Salem Evaluation of radiologist’s knowledge about the Artificial Intelligence in diagnostic radiology: a survey-based study |
title | Evaluation of radiologist’s knowledge about the Artificial Intelligence in diagnostic radiology: a survey-based study |
title_full | Evaluation of radiologist’s knowledge about the Artificial Intelligence in diagnostic radiology: a survey-based study |
title_fullStr | Evaluation of radiologist’s knowledge about the Artificial Intelligence in diagnostic radiology: a survey-based study |
title_full_unstemmed | Evaluation of radiologist’s knowledge about the Artificial Intelligence in diagnostic radiology: a survey-based study |
title_short | Evaluation of radiologist’s knowledge about the Artificial Intelligence in diagnostic radiology: a survey-based study |
title_sort | evaluation of radiologist’s knowledge about the artificial intelligence in diagnostic radiology: a survey-based study |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7412626/ https://www.ncbi.nlm.nih.gov/pubmed/32821436 http://dx.doi.org/10.1177/2058460120945320 |
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