在人工智能时代,国家医学图书馆应该如何发展
1Biomedical Informatics Center, Medical University of South Carolina, Charleston, SC 29405, United States.
概括
国家医学图书馆面临来自人工智能 (AI) 和大型语言模型 (LLM) 的挑战. NLM可以通过成为认证机构,健康科学观测中心或人工智能驱动的翻译和总结的枢纽来适应.
科学领域:
- 信息科学 信息科学 信息科学
- 医疗信息学 医疗信息学
- 科学中的人工智能.
背景情况:
- 人工智能 (AI) 加快和伪造科学发现.
- 人工智能影响数据转化为知识和智慧.
- 人工智能的兴起需要对科学诚信进行重新评估.
研究的目的:
- 描述国家医学图书馆 (NLM) 因人工智能和大型语言模型 (LLM) 而面临的挑战.
- 建议对NLM作为人工智能时代科学知识完整性的守护者进行重组任务.
- 探索人工智能革命对科学信息管理的哲学基础,威胁和机遇.
主要方法:
- 这是一篇关于人工智能对科学过程的影响的观点文章.
- 分析AI在科学中带来的威胁和机遇.
- 关于NLM战略重组和新角色的建议.
主要成果:
- 网络管理系统可以利用信息科学原则来应对人工智能挑战.
- 拟议NLM的三个角色:科学来源认证机构,健康科学观察中心,以及人工智能驱动的翻译和总结的枢纽.
- 这些角色支持各种用户,包括患者,公众,科学家和临床医生.
结论:
- 适应互联网革命增强了NLM的能力.
- 对于NLM来说,大胆的适应策略对于导航人工智能革命至关重要.
- 通过人工智能集成,NLM有可能对促进科学和人类健康产生重大影响.
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