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Volume 14 Issue 6
Nov.  2023
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ZHENG Xinya, HUANG Yunyou, ZHANG Yiting, WENG Shengjie, ZHAN Jianfeng, ZHAGN Zhifei. Medical Artificial Intelligence Standard System: History and Current Status[J]. Medical Journal of Peking Union Medical College Hospital, 2023, 14(6): 1135-1141. DOI: 10.12290/xhyxzz.2023-0428
Citation: ZHENG Xinya, HUANG Yunyou, ZHANG Yiting, WENG Shengjie, ZHAN Jianfeng, ZHAGN Zhifei. Medical Artificial Intelligence Standard System: History and Current Status[J]. Medical Journal of Peking Union Medical College Hospital, 2023, 14(6): 1135-1141. DOI: 10.12290/xhyxzz.2023-0428
shu

Medical Artificial Intelligence Standard System: History and Current Status

  • 1.

    Capital Medical University School of Basic Medical Sciences, Beijing 100069, China

  • 2.

    School of Computer Science and Engineering, Guangxi Normal University, Guilin, Guangxi 541000, China

  • 3.

    Research Center for Advanced Computer Systems, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100086, China

Funds: 

Strategic Priority Research Program of the Chinese Academy of Sciences XDA0320000

Strategic Priority Research Program of the Chinese Academy of Sciences XDA0320300

Guangxi Science and Technology Electric Power Data Analysis Research GuiKe AD20297004

More Information
  • Corresponding author:

    ZHAGN Zhifei, E-mail: zhifeiz@ccmu.edu.cn

  • Received Date: September 10, 2023
  • Accepted Date: October 29, 2023
  • Issue Publish Date: November 29, 2023
    Graphical Abstract
    • Abstract
  • The standardization of medical artificial intelligence (AI) is currently in its infancy and falls short of meeting the needs for the development, deployment, control, assessment, and guidance of medical AI products. This not only makes it difficult to standardize the research and development process and therefore increase the cost and affect the quality of the products, but also leads to challenges in achieving unified interaction, comparison, and evaluation of AI products. It may result in incorrect estimation and evaluation of products, thus misguiding the direction of medical AI development. Consequently, establishing a mature and unified standard system for medical AI has become an urgent priority. To facilitate the advancement of the medical AI standard system from its nascent stage to maturity, we conduct an in-depth analysis of the development history of medical AI standards from four aspects: medical data standards, standard datasets, benchmarks, and norms/guidelines. By revealing the problems in the current medical AI standards, we aim to provide a reference for related research.
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    • References (37)
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