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Development of minimally invasive surgery talent training system enabled by integrated information platform for application demonstration
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Fei Sun1, Xiaoyan Zhang2, Zhichen Wang1, Qian Zhang1, 3, Jiquan Liu2, *, Jingyi Feng1, 3, *
Modern Instruments & Medical Treatment | 2026, 32(4) : 27 - 35
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Modern Instruments & Medical Treatment | 2026, 32(4): 27-35
Development of minimally invasive surgery talent training system enabled by integrated information platform for application demonstration
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Fei Sun1, Xiaoyan Zhang2, Zhichen Wang1, Qian Zhang1, 3, Jiquan Liu2, *, Jingyi Feng1, 3, *
Affiliations
  • 1.Department of Clinical Engineering, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
  • 2.College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou 310000, China
  • 3.Zhejiang Key Laboratory of Clinical Evaluation Technology for Medical Device, Hangzhou 310003, China
Published: 2026-08-10 doi: 10.11876/mimt202604004
Outline
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Objective

In view of the characteristics of context dependence and practical operation emphasized in the training of minimally invasive surgery talents, as well as the problem that the traditional teaching model is unable to meet the standardized and homogeneous training needs of various medical institutions, this study explores the supporting role of the information platform in the application demonstration of domestic innovative high-end minimally invasive surgical medical devices on the talent training system.

Methods

Relying on the national collaborative application demonstration comprehensive information platform, a video teaching module reflecting the core functions of the platform—the laparoscopic surgery video image big data platform and intelligent analysis and processing system was constructed. The former realizes the standardized collection, transcoding and management of surgical videos; the latter, based on deep learning algorithms, realizes functions such as image smoke removal enhancement, surgical scene behavior recognition, workflow sequence analysis, image long-text description generation and synthetic image generation with semantic information. Both are jointly embedded in the training content construction process.

Results

As of October 2025, the platform has cumulatively collected and covered 1,045 clinical surgical videos of 13 surgical types; the supporting user center for trainees has gathered the learning archives of about 500 registered trainees from approximately 300 medical institutions across the country. During the demonstration period, the total learning time reached 2,924 hours, and the total number of video accesses reached 7,565 times; the intelligent analysis function has been applied to representative surgical procedures such as cholecystectomy and partial nephrectomy.

Conclusion

The standardized image data platform can provide information support for the training of minimally invasive surgery talents, and the intelligent analysis function has application value in assisting video observation learning, which can provide practical support for the training of minimally invasive surgery talents, but its efficacy still needs further verification.

Minimally invasive surgery  /  Endoscopic surgery  /  Video imaging big data platform  /  Artificial intelligence  /  Talent training  /  Integrated information platform for application demonstration
孙斐, 张小妍, 王之晨, 张倩, 刘济全, 冯靖祎. 应用示范综合信息平台赋能微创外科人才培养体系建设研究. 现代仪器与医疗, 2026 , 32 (4) : 27 -35 . DOI: 10.11876/mimt202604004
Fei Sun, Xiaoyan Zhang, Zhichen Wang, Qian Zhang, Jiquan Liu, Jingyi Feng. Development of minimally invasive surgery talent training system enabled by integrated information platform for application demonstration[J]. Modern Instruments & Medical Treatment, 2026 , 32 (4) : 27 -35 . DOI: 10.11876/mimt202604004
Year 2026 volume 32 Issue 4
116
14
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Article Info
doi: 10.11876/mimt202604004
  • Receive Date:2026-07-24
  • Online Date:2026-10-23
  • Published:2026-08-10
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  • Received:2026-07-24
Funding
Affiliations
    1.Department of Clinical Engineering, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
    2.College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou 310000, China
    3.Zhejiang Key Laboratory of Clinical Evaluation Technology for Medical Device, Hangzhou 310003, China
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