Volume 12 Issue 5
Sep.  2021
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ZHANG Zhifei, YANG Zhengxin, HUANG Yunyou, ZHAN Jianfeng. Big Medical Data and Medical AI Standards: Status Quo, Opportunities and Challenges[J]. Medical Journal of Peking Union Medical College Hospital, 2021, 12(5): 614-620. doi: 10.12290/xhyxzz.2021-0472
Citation: ZHANG Zhifei, YANG Zhengxin, HUANG Yunyou, ZHAN Jianfeng. Big Medical Data and Medical AI Standards: Status Quo, Opportunities and Challenges[J]. Medical Journal of Peking Union Medical College Hospital, 2021, 12(5): 614-620. doi: 10.12290/xhyxzz.2021-0472

Big Medical Data and Medical AI Standards: Status Quo, Opportunities and Challenges

doi: 10.12290/xhyxzz.2021-0472

Standardization Research Project of Chinese Academy of Sciences BZ201800001

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  • Corresponding author: HUANG Yunyou  Tel: 86-773-8285764, E-mail: huangyunyou@gxnu.edu.cn; ZHAN Jianfeng  Tel: 86-10-62601166, E-mail: zhanjianfeng@ict.ac.cn
  • Received Date: 2021-06-15
  • Accepted Date: 2021-08-23
  • Available Online: 2021-09-16
  • Publish Date: 2021-09-30
  • Big medical data and medical artificial intelligence (AI) not only have the great potential for improving the utilization of medical resources and the quality of medical service, but also pose challenges to privacy protection and technical risks. Standards are the consensus and norms for constructing, evaluating, and applying new technologies. The clinical application of big medical data and medical AI urgently needs regulations on data, systems, measurement standards, and codes of practice for evaluating new technologies. This paper defines big medical data and medical AI standards, including data-related standards, public datasets, benchmarks, codes of practice, and summarizes state-of-the-art and state-of-the-practice of big medical data and medical AI standards. While looking forward to the development prospect of big medical data and medical AI, we propose an innovative architecture consisting of big-data-and-AI-enhanced medical information systems and the big medical science infrastructure.
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