Enhancing puncture skills training with generative AI and digital technologies: a parallel cohort study.

Journal: BMC medical education
PMID: 39563290

Abstract

BACKGROUND: Traditional puncture skills training for refresher doctors faces limitations in effectiveness and efficiency. This study explored the application of generative AI (ChatGPT), templates, and digital imaging to enhance puncture skills training.

Authors

  • Zhe Ji
    China International Neuroscience Institute (China-INI), Beijing, China.
  • Yuliang Jiang
    Department of Radiation Oncology, Peking University Third Hospital, 49th North Garden Road, Haidian District, Beijing, 100191, P.R. China.
  • Haitao Sun
    State Key Laboratory of Precision Spectroscopy, School of Physics and Electronic Science, East China Normal University, 500 Dongchuan Road, Shanghai, 200241, PR China.
  • Bin Qiu
    MOE Key Laboratory for Analytical Science of Food Safety and Biology, Fujian Provincial Key Laboratory of Analysis and Detection for Food Safety, College of Chemistry, Fuzhou University, Fuzhou, Fujian 350116, China.
  • Yi Chen
    Department of Anesthesiology and Perioperative Medicine, General Hospital of Ningxia Medical University, Yinchuan, China.
  • Mao Li
    Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu 610065, P. R. China.
  • Jinghong Fan
    Department of Radiation Oncology, Peking University Third Hospital, 49th North Garden Road, Haidian District, Beijing, 100191, P.R. China.
  • Junjie Wang
    School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China.

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