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Previously submitted to: Journal of Medical Internet Research (no longer under consideration since Oct 28, 2022)

Date Submitted: Oct 4, 2022

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

How do nurses work in the age of Artificial intelligence:Viewpoint

  • Minghui Ye; 
  • Zhongqiu Lu; 
  • Hongyu Sun

ABSTRACT

AI is undoubtedly revolutionizing medical research and patient care with various applications in several fields. Chronic disease nursing care, an important part of clinical management, has benefited much from AI in many ways. It is important to understand the principles that make it workable before using artificial intelligence, not to blindly replace all work with AI. Nurses are the main force of symptom group research, expanding from the diabetes to other chronic disease, they are mainly responsible for patients daily symptom and vital signs record. However, many AI research currently exclude nurses from the development phase and only include them in the use and feedback population. The overall design of the symptom analysis and long-term management approach cannot be done without the guidance and supervision of nurses, but currently nurses are not sufficiently involved, which may be related to the fact that nursing staff have less understanding of AI compared to other researchers and are not yet clear about the value of their role in AI. Therefore, it is very necessary to explore the role points of nurses in symptom analysis and long-term management, and to analyze the breakthrough points of nurses' work in AI in the future by drawing on the latest research in these two areas.


 Citation

Please cite as:

Ye M, Lu Z, Sun H

How do nurses work in the age of Artificial intelligence:Viewpoint

JMIR Preprints. 04/10/2022:43200

DOI: 10.2196/preprints.43200

URL: https://preprints.jmir.org/preprint/43200

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