Impact of artificial intelligence on medical Students’ radiology career choices: a cross-sectional Study at King Faisal University, Saudi Arabia

Mohammed Hazem; Ali Fahmi Alkhars; Sharifah Khalid Almulhim; Omar Saad Alateeq; Razan Mohammed Al Omireen

doi:10.24911/IJMDC.51-1727514213

2024, Vol: 8, Issue: 9

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Original Article
Online Published: 25 Oct 2024

IJMDC. 2024; 8(9):

doi: 10.24911/IJMDC.51-1727514213

Impact of artificial intelligence on medical Students’ radiology career choices: a cross-sectional Study at King Faisal University, Saudi Arabia

Mohammed Hazem, Ali Fahmi Alkhars, Sharifah Khalid Almulhim, Omar Saad Alateeq, Razan Mohammed Al Omireen.

Abstract
Background: Artificial intelligence (AI) is increasingly influencing medical students’ perceptions of radiology as a career. Studies from the United Kingdom, Switzerland, Jordan, and the Middle East reveal that while students acknowledge AI’s growing importance in healthcare, many fear that AI could replace radiologists or reduce job opportunities, impacting their specialty choices. These findings highlight the need for more research and education on AI’s role in radiology and its broader implications for the profession.
Methods: A cross-sectional survey was conducted at King Faisal University, Saudi Arabia, to assess 176 medical students’ knowledge and perceptions of AI in radiology, and how these perceptions influenced their specialty choices. Data were collected through an online questionnaire and analyzed using Statistical Package for the Social Sciences software.
Results: Of the 176 participants, 84.7% were in their clinical years, with an average age of 22.2 years. Only 5.1% of students listed radiology as their top specialty, increasing to 8% if AI were not a factor. A majority (72.2%) had limited knowledge of AI’s role in radiology, with most learning about AI from media and peers. Clinical-year students demonstrated a higher level of AI knowledge, although no significant correlation was found between AI knowledge and the choice of radiology as a specialty. Students expressed a preference for learning about AI through rotations and pre-clinical lectures.
Conclusion: Despite AI’s potential to revolutionize radiology by improving diagnostics and reducing errors, most students showed limited knowledge of AI in the field. Clinical-year students, with more exposure to radiology, had a better understanding of AI’s role. Concerns about AI reducing job opportunities were common, mirroring global trends. Media and peer discussions were the primary sources of AI information, but many students remained unaware of AI’s specific applications in radiology. Overall, AI had a minimal effect on students’ specialty preferences.

Key words: Artificial intelligence, radiology, medical students, specialty choice, King Faisal University, Saudi Arabia, cross-sectional analysis

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How to Cite this Article

Pubmed Style

Hazem M, Alkhars AF, Almulhim SK, Alateeq OS, Omireen RMA. Impact of artificial intelligence on medical Students’ radiology career choices: a cross-sectional Study at King Faisal University, Saudi Arabia. IJMDC. Online First: 25 Oct, 2024. doi:10.24911/IJMDC.51-1727514213

Web Style

Hazem M, Alkhars AF, Almulhim SK, Alateeq OS, Omireen RMA. Impact of artificial intelligence on medical Students’ radiology career choices: a cross-sectional Study at King Faisal University, Saudi Arabia. https://www.ijmdc.com/?mno=222348 [Access: November 27, 2024]. doi:10.24911/IJMDC.51-1727514213

AMA (American Medical Association) Style

Hazem M, Alkhars AF, Almulhim SK, Alateeq OS, Omireen RMA. Impact of artificial intelligence on medical Students’ radiology career choices: a cross-sectional Study at King Faisal University, Saudi Arabia. IJMDC. Online First: 25 Oct, 2024. doi:10.24911/IJMDC.51-1727514213

Vancouver/ICMJE Style

Hazem M, Alkhars AF, Almulhim SK, Alateeq OS, Omireen RMA. Impact of artificial intelligence on medical Students’ radiology career choices: a cross-sectional Study at King Faisal University, Saudi Arabia. IJMDC, [cited November 27, 2024]; Online First: 25 Oct, 2024. doi:10.24911/IJMDC.51-1727514213

Harvard Style

Hazem, M., Alkhars, . A. F., Almulhim, . S. K., Alateeq, . O. S. & Omireen, . R. M. A. (2024) Impact of artificial intelligence on medical Students’ radiology career choices: a cross-sectional Study at King Faisal University, Saudi Arabia. IJMDC, Online First: 25 Oct, 2024. doi:10.24911/IJMDC.51-1727514213

Turabian Style

Hazem, Mohammed, Ali Fahmi Alkhars, Sharifah Khalid Almulhim, Omar Saad Alateeq, and Razan Mohammed Al Omireen. 2024. Impact of artificial intelligence on medical Students’ radiology career choices: a cross-sectional Study at King Faisal University, Saudi Arabia. International Journal of Medicine in Developing Countries, Online First: 25 Oct, 2024. doi:10.24911/IJMDC.51-1727514213

Chicago Style

Hazem, Mohammed, Ali Fahmi Alkhars, Sharifah Khalid Almulhim, Omar Saad Alateeq, and Razan Mohammed Al Omireen. "Impact of artificial intelligence on medical Students’ radiology career choices: a cross-sectional Study at King Faisal University, Saudi Arabia." International Journal of Medicine in Developing Countries Online First: 25 Oct, 2024. doi:10.24911/IJMDC.51-1727514213

MLA (The Modern Language Association) Style

APA (American Psychological Association) Style

Hazem, M., Alkhars, . A. F., Almulhim, . S. K., Alateeq, . O. S. & Omireen, . R. M. A. (2024) Impact of artificial intelligence on medical Students’ radiology career choices: a cross-sectional Study at King Faisal University, Saudi Arabia. International Journal of Medicine in Developing Countries, Online First: 25 Oct, 2024. doi:10.24911/IJMDC.51-1727514213

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