RT Journal Article
SR Electronic
T1 Artificial intelligence in radiology
JF Saudi Medical Journal
JO Saudi Med J
FD Prince Sultan Military Medical City
SP 53
OP 60
DO 10.15537/smj.2022.43.1.20210337
VO 43
IS 1
A1 Mawya A. Khafaji
A1 Mohammed A. Safhi
A1 Roia H. Albadawi
A1 Salma O. Al-Amoudi
A1 Salah S. Shehata
A1 Fadi Toonsi
YR 2022
UL http://smj.org.sa/content/43/1/53.abstract
AB 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.