Radiology residents' perspectives on Artificial Intelligence in Turkiye: knowledge, attitudes, and educational expectations
Abstract
Aims: This study aims to assess the knowledge levels, attitudes, and professional concerns of radiology residents in Turkiye regarding Artificial Intelligence (AI) technologies in medical imaging.
Methods: A cross-sectional, descriptive survey was conducted with 90 radiology residents from various teaching and university hospitals in Turkiye. Data were collected using a structured online questionnaire that evaluated demographics, self-reported AI knowledge, attitudes toward AI integration (using a Likert scale), and educational expectations.
Results: The study revealed that 95.6% of residents had received no formal AI training during their residency. Although 56.7% claimed “basic knowledge” of AI, 70% were unfamiliar with the concept of “algorithmic bias”. Participants viewed AI primarily as a “copilot” (mean score 4.27/5) rather than a threat. While 60% rejected the idea that AI would completely replace radiologists, 77.8% agreed with the statement that “radiologists who use AI will replace those who do not”. Furthermore, 92.2% of participants expressed a desire for specific AI training.
Conclusion: Radiology residents demonstrate a highly enthusiastic and pragmatic attitude toward AI integration; however, a significant gap exists between their perceived competence and actual conceptual literacy. These findings suggest that AI literacy and ethical principles should be urgently integrated as a mandatory module in the core radiology curriculum.
Keywords
References
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Details
Primary Language
English
Subjects
Radiology and Organ Imaging
Journal Section
Research Article
Publication Date
July 20, 2026
Submission Date
March 6, 2026
Acceptance Date
May 20, 2026
Published in Issue
Year 2026 Volume: 9 Number: 4
APA
Ataş, A. E., Erol, S., & Kaya, H. E. (2026). Radiology residents’ perspectives on Artificial Intelligence in Turkiye: knowledge, attitudes, and educational expectations. Journal of Health Sciences and Medicine, 9(4), 866-871. https://izlik.org/JA93MK57CS
AMA
1.Ataş AE, Erol S, Kaya HE. Radiology residents’ perspectives on Artificial Intelligence in Turkiye: knowledge, attitudes, and educational expectations. J Health Sci Med / JHSM. 2026;9(4):866-871. https://izlik.org/JA93MK57CS
Chicago
Ataş, Abdullah Enes, Seyit Erol, and Hasan Emin Kaya. 2026. “Radiology Residents’ Perspectives on Artificial Intelligence in Turkiye: Knowledge, Attitudes, and Educational Expectations”. Journal of Health Sciences and Medicine 9 (4): 866-71. https://izlik.org/JA93MK57CS.
EndNote
Ataş AE, Erol S, Kaya HE (July 1, 2026) Radiology residents’ perspectives on Artificial Intelligence in Turkiye: knowledge, attitudes, and educational expectations. Journal of Health Sciences and Medicine 9 4 866–871.
IEEE
[1]A. E. Ataş, S. Erol, and H. E. Kaya, “Radiology residents’ perspectives on Artificial Intelligence in Turkiye: knowledge, attitudes, and educational expectations”, J Health Sci Med / JHSM, vol. 9, no. 4, pp. 866–871, July 2026, [Online]. Available: https://izlik.org/JA93MK57CS
ISNAD
Ataş, Abdullah Enes - Erol, Seyit - Kaya, Hasan Emin. “Radiology Residents’ Perspectives on Artificial Intelligence in Turkiye: Knowledge, Attitudes, and Educational Expectations”. Journal of Health Sciences and Medicine 9/4 (July 1, 2026): 866-871. https://izlik.org/JA93MK57CS.
JAMA
1.Ataş AE, Erol S, Kaya HE. Radiology residents’ perspectives on Artificial Intelligence in Turkiye: knowledge, attitudes, and educational expectations. J Health Sci Med / JHSM. 2026;9:866–871.
MLA
Ataş, Abdullah Enes, et al. “Radiology Residents’ Perspectives on Artificial Intelligence in Turkiye: Knowledge, Attitudes, and Educational Expectations”. Journal of Health Sciences and Medicine, vol. 9, no. 4, July 2026, pp. 866-71, https://izlik.org/JA93MK57CS.
Vancouver
1.Abdullah Enes Ataş, Seyit Erol, Hasan Emin Kaya. Radiology residents’ perspectives on Artificial Intelligence in Turkiye: knowledge, attitudes, and educational expectations. J Health Sci Med / JHSM [Internet]. 2026 Jul. 1;9(4):866-71. Available from: https://izlik.org/JA93MK57CS
