人工智能对生物医学文献搜索的贡献:革命还是复杂?
Rui Yip1,2, Young Joo Sun1,2, Alexander G Bassuk3
1Molecular Surgery Laboratory, Stanford University, Palo Alto, California, United States of America.
PLOS digital health
|May 12, 2025
概括
像ChatGPT这样的对话性AI显示了科学文献搜索的潜力,但在准确性和相关性方面存在局限性. 用户工具提高了性能,但严格的比较评估对于可靠的AI整合到研究中至关重要.
科学领域:
- 生物医学研究生物医学研究
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 交谈式人工智能,以ChatGPT为例,越来越多地用于科学文献评论和摘要.
- 临床医生和研究人员广泛采用其实用性的比较证据.
- 在科学文献搜索中,需要从最终用户的角度评估人工智能工具.
研究的目的:
- 从临床医生和生物医学研究人员的角度探索ChatGPT在文献搜索中的实用性.
- 量化地比较基本的ChatGPT与传统的搜索引擎 (谷歌,PubMed).
- 评估ChatGPT用户支持工具对各种场景中的文献搜索性能的影响.
主要方法:
- 基本的ChatGPT与谷歌和PubMed在文献搜索中的定量比较.
- 使用用户支持工具 (插件,网页浏览,提示工程,定制GPT) 测试ChatGPT.
- 通过四种场景进行评估:高兴度,利基,假设生成和新兴的临床主题.
主要成果:
- 基本聊天GPT在一致性,准确性和相关性方面表现出局限性.
- 用户支持工具提高了ChatGPT的性能,但局限性仍然存在.
- 不同的搜索场景带来了独特的挑战,包括信息过载和稀缺的文献.
结论:
- 像ChatGPT这样的对话性AI工具对于科学文献搜索具有潜力,但也存在陷.
- 用户支持工具可以减轻一些限制,但不能完全解决它们.
- 在科学研究中广泛整合人工智能之前,严格的比较评估至关重要.
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