AI Summary & Key Takeaways
AI InsightThese findings suggest that AI literacy and ethical principles should be urgently integrated as a mandatory module in the core radiology curriculum.
📌 3 Key Takeaways
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.