南方医科大学学报 ›› 2026, Vol. 46 ›› Issue (7): 1723-1730.doi: 10.12122/j.issn.1673-4254.2026.07.25

• • 上一篇    

人工智能在微创外科手术技能评估与质量控制中的应用研究进展

苏柏尔1,2(), 张颖2, 闫智娴2, 邹颖2, 成禹帆3, 李天舒4, 李晋铭2, 陈晓彤2, 梁春祺5, 徐镕2, 杨晟明6, 彭渤2, 陈豪1(), 余江1(), 胡彦锋1()   

  1. 1.南方医科大学南方医院普通外科//广东省胃肠肿瘤精准微创诊疗重点实验室//广东省微创外科工程技术研究中心,广东 广州 510515
    2.南方医科大学 生物医学工程学院,广东 广州 510515
    4.南方医科大学 生物医学工程学院,广东 广州 510515
    3.南方医科大学深圳临床医学院,广东 深圳 518100
    5.南方医科大学第二临床医学院,广东 广州 510282
    6.南方医科大学广东省人民医院临床医学院,广东 广州 510080
  • 收稿日期:2026-04-02 出版日期:2026-07-20 发布日期:2026-07-20
  • 通讯作者: 陈豪,余江,胡彦锋 E-mail:1424554892@qq.com;chenhao.05@163.com;balbc@163.com;yfenghu@qq.com
  • 作者简介:苏柏尔,南方医科大学临床医学八年制本硕博连读,E-mail: 1424554892@qq.com
    第一联系人:苏柏尔、张 颖、闫智娴、邹 颖共同为第一作者
  • 基金资助:
    国家自然科学基金(82203712);广东省科技创新战略专项资金(大学生科技创新培育)项目(pdjh2024a086);广州市科技计划项目(2025A04J4017)

Application of artificial intelligence for surgical skill assessment and quality control in minimally invasive surgery: progress, problems and prospect

Boer SU1,2(), Ying ZHANG2, Zhixian YAN2, Ying ZOU2, Yufan CHENG3, Tianshu LI4, Jinming LI2, Xiaotong CHEN2, Chunqi LIANG5, Rong XU2, Shengming YANG6, Bo PENG2, Hao CHEN1(), Jiang YU1(), Yanfeng HU1()   

  1. 1.Department of General Surgery, Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Guangdong Provincial Engineering Technology Research Center of Minimally Invasive Surgery, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
    2.First School of Clinical Medicine, Southern Medical University, Guangzhou 510515, China
    4.School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China
    3.Shenzhen School of Clinical Medicine, Southern Medical University, Shenzhen 518100, China
    5.Second School of Clinical Medicine, Southern Medical University, Guangzhou 510282, China
    6.School of Clinical Medicine, Guangdong Provincial People's Hospital, Southern Medical University, Guangzhou 510080, China
  • Received:2026-04-02 Online:2026-07-20 Published:2026-07-20
  • Contact: Hao CHEN, Jiang YU, Yanfeng HU E-mail:1424554892@qq.com;chenhao.05@163.com;balbc@163.com;yfenghu@qq.com
  • Supported by:
    National Natural Science Foundation of China(82203712)

摘要:

随着医学科技的飞速发展,微创手术已成为治疗复杂外科疾病的重要手段。然而,手术具有高风险性以及技术密集型的特征,使得术者操作差异、团队协作效率及突发事件的处理能力成为了影响患者预后的关键因素。目前,建立系统的技能评估与质量控制体系,被认为是降低风险、提高围手术期安全性的关键措施。然而,传统技能评估与质量控制方式(如主观评分、术后分析等)虽然有一定的价值,但是因为标准不一、耗时耗力与缺乏实时反馈等缺点已经难以满足当前外科精准化的需求。近些年来,人工智能(AI)特别是基于计算机视觉的深度学习技术,在手术动作识别、手术流程阶段分析、术中安全监测等方面表现出巨大的潜力,推动了手术技能评估与质量控制自动化、客观化与精准化的发展。本文系统梳理AI在微创外科手术技能评估与质量控制领域的最新研究进展,重点讨论基于AI的技能评估与质量控制算法模型,分析模型泛化性、隐私保护及多中心适用性等问题,并展望未来智能精准外科的临床应用前景。

关键词: 微创外科手术, 技能评估, 质量控制, 人工智能, 深度学习

Abstract:

Minimally invasive surgery has become an important approach for treating complex surgical conditions. As such surgical procedures are often associated with high risks and technical complexities, the surgeon's skills, efficiency of team collaboration, and capacities for emergency response all significantly affect the surgical outcomes. Establishing a robust surgical skill assessment and quality control system is therefore of vital importance to reduce the risks and enhance perioperative safety. In this context, the conventional methods for surgical skill assessment and quality control (e.g., subjective scoring, postoperative analysis, etc.) appear insufficient due to their inconsistent standards, time and labor intensity, and lack of real-time feedback. In recent years, artificial intelligence (AI), particularly computer vision-based deep learning technology, has demonstrated immense potential in surgical motion recognition, workflow phase analysis, and intraoperative safety monitoring, and has propelled the development of surgical skill assessment and quality control toward automation, objectivity, and precision. Herein the authors review the latest research progress in the application of AI in minimally invasive surgical skill assessment and quality control, focusing on AI-based skill assessment and quality control algorithm models. This review also addresses model generalization, privacy protection, multicenter applicability, and future clinical applications of intelligent precision surgery.

Key words: minimally invasive surgery, skill assessment, quality control, artificial intelligence, deep learning