Accepted for/Published in: JMIR Medical Education
Date Submitted: Apr 29, 2023
Date Accepted: Jun 11, 2024
Warning: This is an author submission that is not peer-reviewed or edited.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.
Reforming China's Secondary Vocational Medical Education: Adapting to the Challenges and Opportunities of the AI Era
ABSTRACT
Background:
China's secondary vocational medical education has played a crucial role in cultivating medical staff and improving public health response capabilities. However, the current system relies heavily on traditional methods and struggles to adapt to technological advancements such as artificial intelligence (AI).
Objective:
To explore the impact of AI on medical practice and suggest potential reforms for China's secondary vocational medical education system in response to these advancements.
Methods:
A literature review was conducted to assess the current state of AI in medicine and its implications for medical practice. Based on the findings, suggestions for reforming China's secondary vocational medical education were proposed.
Results:
AI shows great potential in improving diagnostic capabilities, treatment decisions, and patient management. However, it also raises concerns about job loss and the need for medical professionals to adapt to new technologies. To better prepare students for the future, China's secondary vocational medical education should focus on practical experience, skills development, medical ethics, humanities, and AI integration. Continuous assessment and long-term research are essential for evaluating the effectiveness of these reforms.
Conclusions:
By addressing the shortcomings of the current system and embracing AI advancements, China's secondary vocational medical education can better prepare future medical professionals for the challenges and opportunities of an ever-evolving medical landscape.
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.