Impact of artificial intelligence on the future of radiology: A national cross-sectional study among medical students and radiology professionals

The incorporation of artificial intelligence (AI) into radiology has significantly transformed disease detection, treatment planning, and outcome forecasting. Despite its potential to revolutionize the field, the knowledge, attitudes, and practices (KAP) surrounding AI among medical students and radiology professionals in Saudi Arabia are still in the early stages of development. This study aimed to investigate the KAP of medical and radiology professionals in Saudi Arabia regarding the application of AI in radiology. Data were collected through an electronic survey distributed via Google Forms, which reached 1582 participants during the 2024–2025 academic year. The participants included medical and radiology students, radiologists, radiology technicians, and technologists from various regions of the country. The results revealed that 57.8 % of the participants had a basic understanding of AI in radiology, with radiologists exhibiting the highest level of awareness (71.2 %). Females were more likely to recognize the benefits of AI, particularly in automated disease detection (83.5 % vs. 73.9 % in males). Concerns regarding the replacement of radiologists with AI were the most pronounced among radiology students (22.7 %). Participants from the private sector reported higher participation in AI-related courses (60.5 %) and projects (58.7 %) than their public sector counterparts. It has a 79.5 % recognition rate for its role in automated disease detection through imaging tests. Radiologists and radiology students generally expressed positive attitudes toward AI, believing that it could improve diagnostic accuracy and efficiency. However, some participants, particularly radiography students, expressed concerns regarding AI replacing human professionals. This study highlights the importance of refining AI training and fostering a deeper understanding of its potential challenges in radiology. The future of AI in radiology in Saudi Arabia holds great promise, with growing interest despite some concerns.

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Publication Details

Journal
Journal of Radiation Research and Applied Sciences
Published
2025-10-18
DOI
https://doi.org/10.1016/j.jrras.2025.102025
Citations
1
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.65
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article

Impact of artificial intelligence on the future of radiology: A national cross-sectional study among medical students and radiology professionals

Ankita Patel, Sara Albadri, Abbas Khalid, Hanady Elyas Osman et al.
1 citations
Journal of Radiation Research and Applied Sciences
Artificial Intelligence in Healthcare and Education
0.65
article

Impact of artificial intelligence on the future of radiology: A national cross-sectional study among medical students and radiology professionals

Ankita Patel, Sara Albadri, Abbas Khalid, Hanady Elyas Osman, Amal Alsalamah, Nawaf Albasha, Yousser Mohammad, Mohamed Yousef, Amira Ahmed Hakami, Lin Mazen Jolha, Waleed Khaled Daghmash, Zainab Mohammed Takroni
article en
1 citations

Abstract

The incorporation of artificial intelligence (AI) into radiology has significantly transformed disease detection, treatment planning, and outcome forecasting. Despite its potential to revolutionize the field, the knowledge, attitudes, and practices (KAP) surrounding AI among medical students and radiology professionals in Saudi Arabia are still in the early stages of development. This study aimed to investigate the KAP of medical and radiology professionals in Saudi Arabia regarding the application of AI in radiology. Data were collected through an electronic survey distributed via Google Forms, which reached 1582 participants during the 2024–2025 academic year. The participants included medical and radiology students, radiologists, radiology technicians, and technologists from various regions of the country. The results revealed that 57.8 % of the participants had a basic understanding of AI in radiology, with radiologists exhibiting the highest level of awareness (71.2 %). Females were more likely to recognize the benefits of AI, particularly in automated disease detection (83.5 % vs. 73.9 % in males). Concerns regarding the replacement of radiologists with AI were the most pronounced among radiology students (22.7 %). Participants from the private sector reported higher participation in AI-related courses (60.5 %) and projects (58.7 %) than their public sector counterparts. It has a 79.5 % recognition rate for its role in automated disease detection through imaging tests. Radiologists and radiology students generally expressed positive attitudes toward AI, believing that it could improve diagnostic accuracy and efficiency. However, some participants, particularly radiography students, expressed concerns regarding AI replacing human professionals. This study highlights the importance of refining AI training and fostering a deeper understanding of its potential challenges in radiology. The future of AI in radiology in Saudi Arabia holds great promise, with growing interest despite some concerns.

Journal of Radiation Research and Applied SciencesVol. 18(4)
National Ribat University (SD), University of Jeddah (SA), University of Business and Technology (SA)
Openalex Percentile: Top 21%
Artificial Intelligence in Healthcare and Education
0.65
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