shisenzhong. Analysis of the Risks and Governance Strategies for the Application of Generative Artificial Intelligence (GAI) in Primary Healthcare. 2024. biomedRxiv.202408.00053
Analysis of the Risks and Governance Strategies for the Application of Generative Artificial Intelligence (GAI) in Primary Healthcare
Corresponding author: shisenzhong, 139962365@qq.com
DOI: 10.12201/bmr.202408.00053
-
Abstract: Purpose/Significance: This article aims to explore the potential, risks, and governance strategies of Generative Artificial Intelligence (GAI) in enhancing the capacity of primary healthcare services in China. Method/Process: Demonstrate through literature review, current situation analysis, and empirical examples. Result/Conclusion: The relevant policies introduced by the government have provided strong support for the application of GAI in primary healthcare services, but a cautious attitude is taken at this stage. Suggestions include building a high-quality GAI data platform, strengthening algorithm standardization and legal construction, deepening medical risk and ethical supervision, encouraging public participation, and promoting cross disciplinary cooperation to effectively empower primary healthcare services with GAI and improve the overall level of medical services.
Key words: Generative artificial intelligence, primary medical applications, risks and governance strategiesSubmit time: 26 August 2024
Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity. -
图表
-
dongyi, Ran ye, Yu zhong guang. 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.. 2024. doi: 10.12201/bmr.202411.00081
GE Xiaoling. Application of Artificial Intelligence Large Models in Healthcare:a Survey. 2024. doi: 10.12201/bmr.202408.00039
xiejunxiang. The composition of Key Technologies and Application in Medical Artificial Intelligence. 2020. doi: 10.12201/bmr.202005.00243
ZhengYanli, Han Fuhai, LI Shuyu, SU Wenxing. Application Status and Prospect of Artificial Intelligence Large Models in Medicine. 2023. doi: 10.12201/bmr.202312.00027
dongtingting. Study on the safety impact and countermeasures of medical artificial intelligence products on patients. 2020. doi: 10.12201/bmr.202012.00004
Li Ming. Analysis of doctors willingness to use medical artificial intelligence and influencing factors. 2023. doi: 10.12201/bmr.202312.00020
Dong Kun, Yang Fen, Yang Yang. Application and Thinking of Artificial Intelligence in General Practitioner Training. 2023. doi: 10.12201/bmr.202305.00011
Lin Jinyin, Lu Changfeng. Main Stakeholder analysis of the application of artificial intelligence in the field of Medical University Library. 2023. doi: 10.12201/bmr.202303.00001
Li Ping, Sun Liping, Ren He, Li Huaping, Shao Zeguo. Construction of artificial intelligence thinking training course system for medical device specialty. 2020. doi: 10.12201/bmr.202007.00013
Ming Li. Analysis of doctors' willingness to use medical artificial intelligence and influencing factors. 2023. doi: 10.12201/bmr.202307.00001
-
ID Submit time Number Download 1 2024-04-28 bmr.202408.00053V1
Download -
-
Public Anonymous To author only
Get Citation
Article Metrics
- Read: 294
- Download: 2
- Comment: 0