Comprehensive Summary
The study investigated medical students’ perception on the AI-assisted diagnosis of renal cell carcinoma (RCC) based on the WHO 2022 classification. 249 students from West China Hospital were selected for a survey that asked questions about their understanding of RCC subtypes, familiarity with AI-based pathology, and trust in AI tools. Most students believed that AI could improve RCC diagnostic accuracy, specifically in identifying various subtypes of RCC. Many students also supported implementing mandatory AI education in medical school curriculum. Nonetheless, the majority of respondents also showed concern about automation bias and reliance on language models. The most notable finding was the difference in how familiar students were with RCC based on WHO 2022 classification based on the students’ disciplines. 66% of urology students were familiar with the new classification and subtypes, compared to 7.7% of students from other disciplines. Overall, these results highlight the optimism towards integration of AI into medicine, while still revealing concerns about reliability and readiness for practical use.
Outcomes and Implications
The study shows that there is a rise of demands in AI education in medical training. As language models are improving and developing at an exponential rate, many students are recognizing the potential of AI to enhance precision and efficiency in medicine. Also, the observed knowledge gap across disciplines raises concerns about how equally medical students are being exposed to new technologies and diagnostic updates. While RCC falls more within urology and pathology, the difference still shows how medical training could benefit from stronger interdisciplinary education and exposure across different fields. Obviously, AI still has areas for improvement, especially in accuracy and ethical boundaries. Thus, addressing such issues will be essential for safely implementing AI into medical education and clinical practice.