在护理信息学中利用生成性人工智能:来自日本的理论批评和政策创新视角
Kazumi Kubota1,2,3, Miya Aishima4, Takanori Fujita3,5,6,7
1Department of Data Science, Shimonoseki City University, Yamaguchi, Japan.
International nursing review
|September 19, 2025
概括
生成型人工智能 (AI) 为护理信息学提供了变革性的潜力,但成功的整合需要解决数字素养和数据隐私等挑战. 一种平衡创新与教育和道德治理的战略方法对于有效采用至关重要.
科学领域:
- 护理信息学 护理信息学
- 医疗保健中的人工智能
- 卫生政策 卫生政策
背景情况:
- 人工智能 (AI) 的快速发展正在显著影响医疗保健服务.
- 生成型人工智能为改善患者治疗结果和临床决策提供了机会.
- 将人工智能整合到护理实践中需要解决伦理,教育和监管方面的考虑.
研究的目的:
- 在护理信息学中对生成AI集成进行理论批评.
- 为护理人工智能采用提供政策创新前景.
- 根据日本的一项调查和已建立的模型,研究生成性AI在护理中的潜力和挑战.
主要方法:
- 卫生和全球政策研究所在日本进行的2023年全国性调查的分析.
- 对关键研究和基础模型的综合文献审查,如技术接受模型和风险感知框架.
- 理论批评和政策创新观点对生成人工智能集成.
主要成果:
- 生成性人工智能有可能提高医疗保健中的信息获取和服务质量.
- 重要挑战包括数字素养低,责任问题,数据准确性和隐私问题.
- 有效整合需要一个多维战略,包括教育和道德治理.
结论:
- 生成型人工智能对护理信息学具有前景,但需要仔细管理风险.
- 成功的采用取决于平衡创新与强大的监管和教育战略.
- 提高数字素养,澄清责任,确保数据安全,促进协作对于安全的AI集成至关重要.
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