Comparative analysis of artificial intelligence tools for the dissemination of colorectal cancer screening guidelines: a novel perspective on early screening education.

Journal: International journal of surgery (London, England)
Published Date:

Abstract

This study systematically evaluated the effectiveness of three artificial intelligence (AI) tools-ChatGPT-4o, Claude3.5, and DeepSeek-in disseminating colorectal cancer screening guidelines to non-medical populations. Using uniform instructions aligned with the Chinese society of clinical oncology 2024 standards, the AI-generated content was analyzed for accuracy, clarity, and rigor, supplemented by a cross-evaluation mechanism to quantify performance. Key findings revealed that DeepSeek demonstrated superior regional adaptability and logical rigor, while requiring improvements in threshold accuracy; ChatGPT-4o exhibited outdated starting age criteria and oversimplified high-risk population screening protocols; and Claude3.5 provided a comprehensive framework but lacked critical implementation details. All tools effectively translated complex medical guidelines into accessible language, underscoring AI's potential in public health education. However, outputs necessitated clinical validation and ethical oversight to mitigate data biases. The study emphasizes AI's role as an auxiliary tool for medical knowledge dissemination, advocating for continuous algorithmic optimization, multidisciplinary collaboration, and dynamic regulatory mechanisms to ensure alignment with evolving medical standards while balancing scientific precision and public accessibility.

Authors

  • Zheng Zhang
    Key Laboratory of Sustainable and Development of Marine Fisheries, Ministry of Agriculture and Rural Affairs, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, PR China.
  • Zheng-Chao Zhang
    Cancer center, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai, China.
  • Shu-Ping Zhang
    Cancer center, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai, China.
  • Wen-Yu Luan
    Cancer center, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai, China.
  • Shuang Han
    Department of Pathology, Affiliated Hospital of Jiangnan University, No. 1000 Hefeng Road, Wuxi City, Jiangsu Province, 214122, China. han_frost@163.com.
  • Zhen-Xi Xu
    Cancer center, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai, China.
  • Shan-Shan Li
    Cancer center, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai, China.
  • Sheng-Jie Wang
    Cancer center, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai, China.
  • Qi Zhao
  • Yu-Meng Chen
    Cancer center, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai, China.
  • Xin-Yi Yuan
    Cancer center, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai, China.
  • Shu-Yuan Zhang
    Cancer center, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai, China.
  • Xiao-Long Tang
    The Second Department of Gastrointestinal Surgery, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
  • Si-Xiang Lin
    Cancer center, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai, China.
  • Yan-Dong Miao
    Cancer center, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai, China.

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