Impact of an AI-based laparoscopic cholecystectomy coaching program on the surgical performance: a randomized controlled trial.

Journal: International journal of surgery (London, England)
PMID:

Abstract

BACKGROUND: Laparoscopic cholecystectomy (LC) is the gold standard for treating symptomatic gallstones but carries inherent risks like bile duct injury. While the critical view of safety (CVS) is advocated to mitigate bile duct injury, its real-world adoption is limited. Additionally, significant variations in surgeon performance impede procedural standardization, highlighting the need for a feasible, innovative, and effective training approach. The aim of this study is to develop an artificial intelligence (AI)-assisted coaching program for LC to enhance surgical education and improve surgeon's performance.

Authors

  • Shangdi Wu
    West China School of Medicine, West China Hospital of Sichuan University, Chengdu, China.
  • Ming Tang
    Business School, Sichuan University, Chengdu 610064, China. tangming0716@163.com.
  • Jie Liu
    School of Bioscience and Bioengineering, South China University of Technology, Guangzhou, China.
  • Dian Qin
    College of Computer Science and Technology, Zhejiang University, Hangzhou, Zhejiang, China.
  • Yuxian Wang
    School of Computer Science, Northwestern Polytechnical University, Xi'an 710072, China.
  • Siwei Zhai
    ChengDu Withai Innovations Technology Company, Chengdu.
  • Enxu Bi
    Department of General Surgery, Qingdao West Coast New Area Central Hospital, Qingdao, Shandong.
  • Yichuan Li
    Hepatobiliary and Pancreatic Surgery, Guang'an People's Hospital, Guang'an.
  • Chunrong Wang
    Department of Hepatobiliary Surgery, Xuanhan People's Hospital, Dazhou.
  • Yong Xiong
    Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China.
  • Guangkuo Li
    Department of Hepatobiliary Surgery, Chengdu Second People's Hospital.
  • Fengwei Gao
    Liver Transplantation Center, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center of Biotherapy, Chengdu, People's Republic of China.
  • Yunqiang Cai
    Department of Pancreatic Surgery, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu, Sichuan 610041 China.
  • Pan Gao
    College of Information Science and Technology, Shihezi University, Shihezi 832003, China.
  • Zhong Wu
    Department of Urology, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Rd, Shanghai, 200040, People's Republic of China. drzhongwu2020@163.com.
  • He Cai
  • Jian Liu
    Department of Rheumatology, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, Anhui, China.
  • Yonghua Chen
    Department of Mechanical Engineering, The University of Hong Kong , Hong Kong, China .
  • Chihua Fang
    Guangdong Provincial Clinical and Engineering Center of Digital Medicine, The First Department of Hepatobiliary Surgery Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, China. fangch_dr@163.com.
  • Li Yao
    College of Information Science and Technology, Beijing Normal University, Beijing, China.
  • Jingwen Jiang
    College of Computer Science, Sichuan University, No. 24 South Section 1, Yihuan Road, Chengdu, Sichuan 610065, P. R. China.
  • Bing Peng
    Department of Pancreatic Surgery, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu, Sichuan 610041 China.
  • Hong Wu
    Department of Liver Surgery, Liver Transplantation Division, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
  • Ang Li
    Section of Hematology-Oncology, Department of Medicine, Baylor College of Medicine, Houston, Texas; Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, Washington. Electronic address: ang.li2@bcm.edu.
  • Xin Wang
    Key Laboratory of Bio-based Material Science & Technology (Northeast Forestry University), Ministry of Education, Harbin 150040, China.