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. 2022 Mar 21;4(1):20210029.
doi: 10.1259/bjro.20210029. eCollection 2022.

A qualitative study to explore opinions of Saudi Arabian radiologists concerning AI-based applications and their impact on the future of the radiology

Walaa Alsharif, Abdulaziz Qurashi  1 , Fadi Toonsi  2 , Ali Alanazi, Fahad Alhazmi  1 , Osamah Abdulaal  1 , Shrooq Aldahery  3 , Khalid Alshamrani
Affiliations

A qualitative study to explore opinions of Saudi Arabian radiologists concerning AI-based applications and their impact on the future of the radiology

Walaa Alsharif et al. BJR Open. .

Abstract

Objective: The aim of this study was to explore opinions and views towards radiology AI among Saudi Arabian radiologists including both consultants and trainees.

Methods: A qualitative approach was adopted, with radiologists working in radiology departments in the Western region of Saudi Arabia invited to participate in this interview-based study. Semi-structured interviews (n = 30) were conducted with consultant radiologists and trainees. A qualitative data analysis framework was used based on Miles and Huberman's philosophical underpinnings.

Results: Several factors, such as lack of training and support, were attributed to the non-use of AI-based applications in clinical practice and the absence of radiologists' involvement in AI development. Despite the expected benefits and positive impacts of AI on radiology, a reluctance to use AI-based applications might exist due to a lack of knowledge, fear of error and concerns about losing jobs and/or power. Medical students' radiology education and training appeared to be influenced by the absence of a governing body and training programmes.

Conclusion: The results of this study support the establishment of a governing body or national association to work in parallel with universities in monitoring training and integrating AI into the medical education curriculum and residency programmes.

Advances in knowledge: An extensive debate about AI-based applications and their potential effects was noted, and considerable exceptions of transformative impact may occur when AI is fully integrated into clinical practice. Therefore, future education and training programmes on how to work with AI-based applications in clinical practice may be recommended.

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Conflict of interest statement

Conflict of interest: We certify that there is no actual or potential conflict of interest in relation to this article (there are none).

Figures

Figure 1.
Figure 1.
Qualitative framework: Miles and Huberman to ensure that the interview is efficient and that the data gathered are as rich, accurate and close as possible to reflecting the real phenomena being studied.
Figure 2.
Figure 2.
Conceptual map for the future of AI-based applications and their impact on the radiology profession
See this image and copyright information in PMC

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