Evaluating the Performance of State-of-the-Art Artificial Intelligence Chatbots Based on the WHO Global Guidelines for the Prevention of Surgical Site Infection: Cross-Sectional Study.

Journal: Journal of medical Internet research
Published Date: Jul 31, 2025

Abstract

BACKGROUND: Surgical site infection (SSI) is the most prevalent type of health care-associated infection that leads to increased morbidity and mortality and a significant economic burden. Effective prevention of SSI relies on surgeons strictly following the latest clinical guidelines and implementing standardized and multilevel intervention strategies. However, the frequent updates to clinical guidelines render the processes of acquisition and interpretation quite time-consuming and intricate. The emergence of artificial intelligence (AI) chatbots offers both possibilities and challenges to address these issues in the surgical field.

Authors

  • Tianyi Wang
    College of Physical Education, Qiqihar University, Qiqihar 161000, China.
  • Ruiyuan Chen
    Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
  • Baodong Wang
    College of Mechanical and Transportation Engineering, China University of Petroleum, Beijing, China.
  • Congying Zou
    Department of Orthopedics, Beijing Chaoyang Hospital, Capital Medical University, 5 JingYuan Road, Shijingshan District, Beijing, 100043, China.
  • Ning Fan
    Department of Orthopedics, Beijing Chaoyang Hospital, Capital Medical University, 5 JingYuan Road, Shijingshan District, Beijing, 100043, China.
  • Shuo Yuan
  • Aobo Wang
    Department of Orthopedics, Beijing Chaoyang Hospital, Capital Medical University, 5 JingYuan Road, Shijingshan District, Beijing, 100043, China.
  • Yu Xi
    Department of endocrinology, Huangshan city People's Hospital, Huangshan 245000, China.
  • Lei Zang
    Department of Orthopedics, Beijing Chaoyang Hospital, Capital Medical University, 5 JingYuan Road, Shijingshan District, Beijing, 100043, China. zanglei@ccmu.edu.cn.

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