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

• Published in: BJR open Vol. 4; no. 1; p. 20210029
• Main Authors: Alsharif, Walaa, Qurashi, Abdulaziz, Toonsi, Fadi, Alanazi, Ali, Alhazmi, Fahad, Abdulaal, Osamah, Aldahery, Shrooq, Alshamrani, Khalid
• Format: Journal Article
• Language: English
• Published: England The British Institute of Radiology 2022
• Subjects: Original Research
• ISSN: 2513-9878; 2513-9878
• DOI: 10.1259/bjro.20210029

The aim of this study was to explore opinions and views towards radiology AI among Saudi Arabian radiologists including both consultants and trainees.
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 (
= 30) were conducted with consultant radiologists and trainees. A qualitative data analysis framework was used based on Miles and Huberman's philosophical underpinnings.
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.
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.
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.