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Artificial intelligence in radiology: Are Saudi residents ready, prepared, and knowledgeable?

OBJECTIVES: To assess the knowledge and perception of artificial intelligence (AI) among radiology residents across Saudi Arabia and assess their interest in learning about AI. METHODS: An observational cross-sectional study carried out among radiology residents enrolled in the Saudi Board of Radiol...

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Autores principales: Khafaji, Mawya A., Safhi, Mohammed A., Albadawi, Roia H., Al-Amoudi, Salma O., Shehata, Salah S., Toonsi, Fadi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Saudi Medical Journal 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9280560/
https://www.ncbi.nlm.nih.gov/pubmed/35022284
http://dx.doi.org/10.15537/smj.2022.43.1.20210337
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author Khafaji, Mawya A.
Safhi, Mohammed A.
Albadawi, Roia H.
Al-Amoudi, Salma O.
Shehata, Salah S.
Toonsi, Fadi
author_facet Khafaji, Mawya A.
Safhi, Mohammed A.
Albadawi, Roia H.
Al-Amoudi, Salma O.
Shehata, Salah S.
Toonsi, Fadi
author_sort Khafaji, Mawya A.
collection PubMed
description OBJECTIVES: To assess the knowledge and perception of artificial intelligence (AI) among radiology residents across Saudi Arabia and assess their interest in learning about AI. METHODS: An observational cross-sectional study carried out among radiology residents enrolled in the Saudi Board of Radiology, Saudi Arabia. An anonymized, self-administered questionnaire was distributed in April 2020 and responses were collected until July 2020. RESULTS: A total of 154 residents filled the questionnaire. The top 3 aspects of AI participants wanted to learn were: clinical use of AI applications, advantages and limitations of AI applications, and technical methods. Approximately 43.5% of participants did not expect AI to affect job positions, while 42% anticipated that job positions will decrease. Approximately 53% expected a reduction in reporting workload, while 28% expected an increase in workload. CONCLUSION: Currently, the exposure of radiologists to the use of AI is inadequate. It is imperative that AI is introduced to radiology trainees and that radiologists stay updated with advances in AI to be more knowledgeable on how to benefit from it.
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spelling pubmed-92805602022-07-20 Artificial intelligence in radiology: Are Saudi residents ready, prepared, and knowledgeable? Khafaji, Mawya A. Safhi, Mohammed A. Albadawi, Roia H. Al-Amoudi, Salma O. Shehata, Salah S. Toonsi, Fadi Saudi Med J Original Articles OBJECTIVES: To assess the knowledge and perception of artificial intelligence (AI) among radiology residents across Saudi Arabia and assess their interest in learning about AI. METHODS: An observational cross-sectional study carried out among radiology residents enrolled in the Saudi Board of Radiology, Saudi Arabia. An anonymized, self-administered questionnaire was distributed in April 2020 and responses were collected until July 2020. RESULTS: A total of 154 residents filled the questionnaire. The top 3 aspects of AI participants wanted to learn were: clinical use of AI applications, advantages and limitations of AI applications, and technical methods. Approximately 43.5% of participants did not expect AI to affect job positions, while 42% anticipated that job positions will decrease. Approximately 53% expected a reduction in reporting workload, while 28% expected an increase in workload. CONCLUSION: Currently, the exposure of radiologists to the use of AI is inadequate. It is imperative that AI is introduced to radiology trainees and that radiologists stay updated with advances in AI to be more knowledgeable on how to benefit from it. Saudi Medical Journal 2022-01 /pmc/articles/PMC9280560/ /pubmed/35022284 http://dx.doi.org/10.15537/smj.2022.43.1.20210337 Text en Copyright: © Saudi Medical Journal https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access journal and articles published are distributed under the terms of the Creative Commons Attribution-NonCommercial License (CC BY-NC). Readers may copy, distribute, and display the work for non-commercial purposes with the proper citation of the original work.
spellingShingle Original Articles
Khafaji, Mawya A.
Safhi, Mohammed A.
Albadawi, Roia H.
Al-Amoudi, Salma O.
Shehata, Salah S.
Toonsi, Fadi
Artificial intelligence in radiology: Are Saudi residents ready, prepared, and knowledgeable?
title Artificial intelligence in radiology: Are Saudi residents ready, prepared, and knowledgeable?
title_full Artificial intelligence in radiology: Are Saudi residents ready, prepared, and knowledgeable?
title_fullStr Artificial intelligence in radiology: Are Saudi residents ready, prepared, and knowledgeable?
title_full_unstemmed Artificial intelligence in radiology: Are Saudi residents ready, prepared, and knowledgeable?
title_short Artificial intelligence in radiology: Are Saudi residents ready, prepared, and knowledgeable?
title_sort artificial intelligence in radiology: are saudi residents ready, prepared, and knowledgeable?
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9280560/
https://www.ncbi.nlm.nih.gov/pubmed/35022284
http://dx.doi.org/10.15537/smj.2022.43.1.20210337
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