Artificial intelligence-assisted diagnosis of renal cell carcinoma: medical students’ perceptions, attitudes, and educational needs_West China Medical Journal

Authors：

ZHANG Xingming ¹ , SHI Xu ¹ , HE Yuxi ¹ , SHEN Pengfei ¹ , ZENG Hao ¹ ,  YIN Xiaoxue ²

1. Department of Urology, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P. R. China;
2. Department of Pathology, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P. R. China;

Corresponding author：

YIN Xiaoxue, Email: xiaoxueyin10@163.com

Keywords：

Artificial intelligence; renal cell carcinoma; medical education; pathological diagnosis

DOI：

10.7507/1002-0179.202506089

Video：

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Objective To evaluate medical students’ perceptions and attitudes toward artificial intelligence (AI)-assisted diagnosis of renal cell carcinoma (RCC), and to analyze their educational needs regarding AI in pathological diagnosis. Methods A questionnaire survey (including closed and open-ended questions) was conducted to assess medical students’ perceptions, attitudes, and educational needs concerning AI-assisted RCC diagnosis. Participants included medical students from different specialties and standardized training residents. The questionnaire covered demographic information, perceptions and attitudes toward AI, and AI-related educational needs. Results A total of 249 respondents completed the survey. The majority were standardized training residents, mostly aged 23-26 years, and 40.96% had practical experience in pathological diagnosis of RCC. The median scores for most closed-ended questions were 4. Respondents generally considered “efficiency” and “improved accuracy” as the most prominent advantages of AI, with timeliness, automated diagnosis, reduction of human error, and precise diagnosis being the most emphasized aspects. Analysis of AI-related educational needs revealed high-frequency keywords such as “expanding sample size” “balanced responsibility allocation” and “enhancing collaboration skills.” Conclusion Medical students hold a positive attitude toward AI and its application in RCC diagnosis, but there remains a lack of formal AI-related education.

Citation： ZHANG Xingming, SHI Xu, HE Yuxi, SHEN Pengfei, ZENG Hao, YIN Xiaoxue. Artificial intelligence-assisted diagnosis of renal cell carcinoma: medical students’ perceptions, attitudes, and educational needs. West China Medical Journal, 2025, 40(9): 1490-1494. doi: 10.7507/1002-0179.202506089 Copy

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West China Medical Journal

Artificial intelligence-assisted diagnosis of renal cell carcinoma: medical students’ perceptions, attitudes, and educational needs

Abstract Full text Figures/Tables Video References Cited by

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