Research on the current status of medical artificial intelligence application risk research and its identification in China.Dong yi1,Ran ye1,Yu zhong guang2,3.

Corresponding author: Yu zhong guang, yzg081892@163.com

DOI: 10.12201/bmr.202411.00081

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  Abstract: Objective: To sort out the current status of medical artificial intelligence risk research in China, conduct risk identification, and propose risk response strategies in a targeted manner. Methods: Through the bibliometric method to search the CNKI academic journal database for relevant research results from 2015 to 2024, and the visualization analysis of the number of publications and keyword co-occurrence relationship, we identified that the research hotspots of medical artificial intelligence in China mainly focus on the technical and data security risks, ethical and legal risks, and risk governance research, and we summarized and proposed a theoretical framework for the identification of medical artificial intelligence risks from environment, organization, technology, and individual levels for the first time, based on the TOE theory and the text Based on the TOE theory and text analysis method, the theoretical framework of medical artificial intelligence risk identification is summarized and proposed for the first time from the four levels of environment,organization, technology, and individual, and a total of 24 specific risks are identified. Conclusion: Subsequently, we should propose specific risk response strategies in terms of pre-social regulation, medical organisation perspectives, and technological applications to guarantee the safe and sustainable development of medical artificial intelligence applications.The contributions of this study are summarized from both theoretical and practical perspectives, starting from the pre-social regulation, healthcare organization perspective, technological applications, and the scope of individual obligations, in order to guarantee the safe and sustainable development of medical artificial intelligence applications.

  Key words: Medical artificial intelligence; current state of risk research; TOE theory; risk identification

  Submit time: 29 November 2024

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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