AI-assisted diagnosis of renal cell carcinoma: educational needs and cognitive assessment based on the WHO classification 2022

This study explored medical students' perceptions, educational needs, and cognitive biases toward Artificial Intelligence-assisted (AI-assisted) renal cell carcinoma (RCC) diagnosis, using the World Health Organization (WHO) 2022 classification. A cross-sectional survey of 249 students examined their familiarity with AI tools, trust in AI-based pathology, and understanding of diagnostic criteria. While most students acknowledged AI's potential to boost diagnostic accuracy, especially for subtyping, over half voiced significant concerns about risks such as over-reliance and automation bias. A key finding was the knowledge gap around the WHO 2022 standards; urology students had a 66.7% self-reported awareness compared to just 7.7% among other majors' students. Nearly 70% of the participants called for mandatory AI training in curricula, with a focus on the rigorous clinical validation of AI tools, supported by over 70% of the pathology students. These results highlight the need to integrate AI innovations with stronger validation protocols and curricular updates to address challenges such as technical limitations, data standardization, and ethical issues. Future studies should align AI development with educational reforms and ethical frameworks to advance precise RCC diagnosis.

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Publication Details

Journal
BMC Medical Education
Published
2025-10-02
DOI
https://doi.org/10.1186/s12909-025-07965-3
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
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article

AI-assisted diagnosis of renal cell carcinoma: educational needs and cognitive assessment based on the WHO classification 2022

Xingming Zhang, Xu Shi, Yan He, Xiaoxue Yin et al.
BMC Medical Education
Artificial Intelligence in Healthcare and Education
article

AI-assisted diagnosis of renal cell carcinoma: educational needs and cognitive assessment based on the WHO classification 2022

Xingming Zhang, Xu Shi, Yan He, Xiaoxue Yin, Qian Wang
article en

Abstract

This study explored medical students' perceptions, educational needs, and cognitive biases toward Artificial Intelligence-assisted (AI-assisted) renal cell carcinoma (RCC) diagnosis, using the World Health Organization (WHO) 2022 classification. A cross-sectional survey of 249 students examined their familiarity with AI tools, trust in AI-based pathology, and understanding of diagnostic criteria. While most students acknowledged AI's potential to boost diagnostic accuracy, especially for subtyping, over half voiced significant concerns about risks such as over-reliance and automation bias. A key finding was the knowledge gap around the WHO 2022 standards; urology students had a 66.7% self-reported awareness compared to just 7.7% among other majors' students. Nearly 70% of the participants called for mandatory AI training in curricula, with a focus on the rigorous clinical validation of AI tools, supported by over 70% of the pathology students. These results highlight the need to integrate AI innovations with stronger validation protocols and curricular updates to address challenges such as technical limitations, data standardization, and ethical issues. Future studies should align AI development with educational reforms and ethical frameworks to advance precise RCC diagnosis.

BMC Medical EducationVol. 25(1)
Sichuan University (CN), West China Hospital of Sichuan University (CN)
Openalex Percentile: Top 80%
Artificial Intelligence in Healthcare and Education
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AI-assisted diagnosis of renal cell carcinoma: educational needs and cognitive assessment based on the WHO classification 2022 — Xingming Zhang, Xu Shi, et al. · BMC Medical Education (2025) | TGRS Research Map | TGRS