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Tytuł:
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Artificial intelligence in radiology: Are Saudi residents ready, prepared, and knowledgeable?
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Autorzy:
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Khafaji MA; From the Department of Radiology (Khafaji, Toonsi), Faculty of Medicine, King Abdulaziz University, from the Department of Radiodiagnostics and Medical Imaging (Albadawi), King Abdulaziz Medical City, from the Department of Radiodiagnostics and Medical Imaging (Shehata), King Faisal Specialist Hospital and Research Centre, Jeddah, and from the Department of Radiodiagnostics and Medical Imaging (Al-Amoudi, Safhi), Prince Sultan Military Medical City, Riyadh, Kingdom of Saudi Arabia.
Safhi MA; From the Department of Radiology (Khafaji, Toonsi), Faculty of Medicine, King Abdulaziz University, from the Department of Radiodiagnostics and Medical Imaging (Albadawi), King Abdulaziz Medical City, from the Department of Radiodiagnostics and Medical Imaging (Shehata), King Faisal Specialist Hospital and Research Centre, Jeddah, and from the Department of Radiodiagnostics and Medical Imaging (Al-Amoudi, Safhi), Prince Sultan Military Medical City, Riyadh, Kingdom of Saudi Arabia.
Albadawi RH; From the Department of Radiology (Khafaji, Toonsi), Faculty of Medicine, King Abdulaziz University, from the Department of Radiodiagnostics and Medical Imaging (Albadawi), King Abdulaziz Medical City, from the Department of Radiodiagnostics and Medical Imaging (Shehata), King Faisal Specialist Hospital and Research Centre, Jeddah, and from the Department of Radiodiagnostics and Medical Imaging (Al-Amoudi, Safhi), Prince Sultan Military Medical City, Riyadh, Kingdom of Saudi Arabia.
Al-Amoudi SO; From the Department of Radiology (Khafaji, Toonsi), Faculty of Medicine, King Abdulaziz University, from the Department of Radiodiagnostics and Medical Imaging (Albadawi), King Abdulaziz Medical City, from the Department of Radiodiagnostics and Medical Imaging (Shehata), King Faisal Specialist Hospital and Research Centre, Jeddah, and from the Department of Radiodiagnostics and Medical Imaging (Al-Amoudi, Safhi), Prince Sultan Military Medical City, Riyadh, Kingdom of Saudi Arabia.
Shehata SS; From the Department of Radiology (Khafaji, Toonsi), Faculty of Medicine, King Abdulaziz University, from the Department of Radiodiagnostics and Medical Imaging (Albadawi), King Abdulaziz Medical City, from the Department of Radiodiagnostics and Medical Imaging (Shehata), King Faisal Specialist Hospital and Research Centre, Jeddah, and from the Department of Radiodiagnostics and Medical Imaging (Al-Amoudi, Safhi), Prince Sultan Military Medical City, Riyadh, Kingdom of Saudi Arabia.
Toonsi F; From the Department of Radiology (Khafaji, Toonsi), Faculty of Medicine, King Abdulaziz University, from the Department of Radiodiagnostics and Medical Imaging (Albadawi), King Abdulaziz Medical City, from the Department of Radiodiagnostics and Medical Imaging (Shehata), King Faisal Specialist Hospital and Research Centre, Jeddah, and from the Department of Radiodiagnostics and Medical Imaging (Al-Amoudi, Safhi), Prince Sultan Military Medical City, Riyadh, Kingdom of Saudi Arabia.
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Źródło:
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Saudi medical journal [Saudi Med J] 2022 Jan; Vol. 43 (1), pp. 53-60.
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Typ publikacji:
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Journal Article; Observational Study
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Język:
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English
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Imprint Name(s):
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Publication: Riyadh : Medical Services Department, Saudi Arabian Armed Forces, Ministry Of Defence And Aviation
Original Publication: Riyadh, Saudi Arabia, Riyadh Al-Kharj Hospital Programme.
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MeSH Terms:
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Artificial Intelligence*
Radiology*
Cross-Sectional Studies ; Humans ; Radiologists ; Saudi Arabia
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References:
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Contributed Indexing:
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Keywords: artificial intelligence; medical imaging; radiology
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Entry Date(s):
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Date Created: 20220113 Date Completed: 20220114 Latest Revision: 20220721
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Update Code:
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20240104
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PubMed Central ID:
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PMC9280560
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DOI:
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10.15537/smj.2022.43.1.20210337
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PMID:
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35022284
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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.
(Copyright: © Saudi Medical Journal.)
