Integrating blockchain technology with artificial intelligence for the diagnosis of tibial plateau fractures.

Journal: European journal of trauma and emergency surgery : official publication of the European Trauma Society
PMID: 39984717

Abstract

PURPOSE: The application of artificial intelligence (AI) in healthcare has seen widespread implementation, with numerous studies highlighting the development of robust algorithms. However, limited attention has been given to the secure utilization of raw data for medical model training, and its subsequent impact on clinical decision-making and real-world applications. This study aims to assess the feasibility and effectiveness of an advanced diagnostic model that integrates blockchain technology and AI for the identification of tibial plateau fractures (TPFs) in emergency settings.

Authors

  • Yi Xie
    Department of Plastic Surgery Peninsula Health Melbourne Victoria Australia.
  • Xiaoliang Chen
    State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, No.28, Xianning West Road, Xi'an, Shaanxi 710049, P.R. China.
  • Huiwen Yang
    Laboratory of Intelligent Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Honglin Wang
    Department of Orthopedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Hong Zhou
    Department of TCM Orthopedics & Traumatology, Gansu province hospital of TCM, Lanzhou, China.
  • Lin Lu
    School of Economics and Management, Guangxi Normal University, Guilin, China.
  • Jiayao Zhang
    Department of Orthopedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Pengran Liu
    Department of Orthopedics Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. lprlprlprwd@163.com.
  • Zhewei Ye
    Department of Orthopedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. yezhewei@hust.edu.cn.

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