Evaluation of the Impact of Artificial Intelligence on Clinical Practice of Radiology in Saudi Arabia

8Citations
Citations of this article
29Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Background: Artificial Intelligence (AI) is becoming integral to the health sector, particularly radiology, because it enhances diagnostic accuracy and optimizes patient care. This study aims to assess the awareness and acceptance of AI among radiology professionals in Saudi Arabia, identifying the educational and training needs to bridge knowledge gaps and enhance AI-related competencies. Methods: This cross-sectional observational study surveyed radiology professionals across various hospitals in Saudi Arabia. Participants were recruited through multiple channels, including direct invitations, emails, social media, and professional societies. The survey comprised four sections: demographic details, perceptions of AI, knowledge about AI, and willingness to adopt AI in clinical practice. Results: Out of 374 radiology professionals surveyed, 45.2% acknowledged AI’s significant impact on their field. Approximately 44% showed enthusiasm for AI adoption. However, 58.6% reported limited AI knowledge and inadequate training, with 43.6% identifying skill development and the complexity of AI educational programs as major barriers to implementation. Conclusion: While radiology professionals in Saudi Arabia are generally positive about integrating AI into clinical practice, significant gaps in knowledge and training need to be addressed. Tailored educational programs are essential to fully leverage AI’s potential in improving medical imaging practices and patient care outcomes.

Cite

CITATION STYLE

APA

Hamd, Z. Y., Alorainy, A. I., Aldhahi, M. I., Gareeballah, A., Alsubaie, N. F., Alshanaiber, S. A., … Abuzaid, M. M. (2024). Evaluation of the Impact of Artificial Intelligence on Clinical Practice of Radiology in Saudi Arabia. Journal of Multidisciplinary Healthcare, 17, 4745–4756. https://doi.org/10.2147/JMDH.S465508

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free