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Background <p>Artificial intelligence (AI) is currently widely applied across various fields, especially in the field of education where it holds significant implications. This systematic review aims to explore the specific role of AI in urological education.</p> Methods <p>Following the PRISMA 2020 guidelines, we searched the PubMed, Scopus, and Web of Science databases for articles related to AI in urological education published up to February 10, 2026. The quality of included studies was assessed using the Medical Education Research Study Quality Instrument (MERSQI), and educational outcomes were classified based on the modified Kirkpatrick framework.</p> Results <p>A total of 15 eligible study records were finally included. The use of AI in urology education can be categorized into two groups: interventions that are used directly in the educational process, and enabling technologies that provide support for education. It was showed that combining AI in urology education had a positive impact on both learners and teachers. For learners such as medical students, urology residents, or interns, the AI-based hybrid teaching model increased learning efficiency and improved students’ theoretical exam scores. Meanwhile, the combination of high-fidelity virtual reality simulation training and intelligent AI feedback showed potential in facilitating the acquisition of clinical skills, in which simulation scores were positively correlated with surgical potential. On the other hand, as the supporting or enabling technology, AI assisted teachers in designing teaching materials and developing assessment programs. In terms of evaluating learners’ performance, AI provided fair and objective evaluation results. In addition, machine learning and computer vision algorithms incorporating AI could automatically recognize surgical steps with high precision.</p> Conclusion <p>The application of AI possesses the capacity to drive transformative changes in urological education. AI can serve as an effective tool to improve students’ learning efficiency, theoretical knowledge level and clinical skills through assisted teaching. Moreover, as the enabling technology, the application of AI may be potential in providing support during the teaching process. But AI should be utilized in a responsible and ethical manner.</p>

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Artificial intelligence in urological education: a systematic review

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月15日

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  • Guanchen Liu,
  • Long Xu,
  • Jue Gong,
  • Guangming Yin,
  • Peng Yuan

摘要

Background

Artificial intelligence (AI) is currently widely applied across various fields, especially in the field of education where it holds significant implications. This systematic review aims to explore the specific role of AI in urological education.

Methods

Following the PRISMA 2020 guidelines, we searched the PubMed, Scopus, and Web of Science databases for articles related to AI in urological education published up to February 10, 2026. The quality of included studies was assessed using the Medical Education Research Study Quality Instrument (MERSQI), and educational outcomes were classified based on the modified Kirkpatrick framework.

Results

A total of 15 eligible study records were finally included. The use of AI in urology education can be categorized into two groups: interventions that are used directly in the educational process, and enabling technologies that provide support for education. It was showed that combining AI in urology education had a positive impact on both learners and teachers. For learners such as medical students, urology residents, or interns, the AI-based hybrid teaching model increased learning efficiency and improved students’ theoretical exam scores. Meanwhile, the combination of high-fidelity virtual reality simulation training and intelligent AI feedback showed potential in facilitating the acquisition of clinical skills, in which simulation scores were positively correlated with surgical potential. On the other hand, as the supporting or enabling technology, AI assisted teachers in designing teaching materials and developing assessment programs. In terms of evaluating learners’ performance, AI provided fair and objective evaluation results. In addition, machine learning and computer vision algorithms incorporating AI could automatically recognize surgical steps with high precision.

Conclusion

The application of AI possesses the capacity to drive transformative changes in urological education. AI can serve as an effective tool to improve students’ learning efficiency, theoretical knowledge level and clinical skills through assisted teaching. Moreover, as the enabling technology, the application of AI may be potential in providing support during the teaching process. But AI should be utilized in a responsible and ethical manner.