在围产学中整合生成人工智能:应用文献评论的应用
Rodrigo Ayala-Yáñez1, Amos Grünebaum2, Frank A Chervenak2
1Centro Médico ABC I.A.P., Mexico City, Mexico.
Journal of perinatal medicine
|September 22, 2025
概括
生成型人工智能 (GAI) 工具可以通过总结研究和比较指南来帮助围产学,提高效率. 然而,临床医生必须确保人工智能素养和监督,以减轻不准确引用等风险.
科学领域:
- 周围生理学 周围生理学
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 临床文献的快速增长挑战了围产科医生保持最新状态的能力.
- 生成型人工智能 (GAI) 工具为管理这种信息过载提供了潜在的解决方案.
研究的目的:
- 评估GAI工具 (ChatGPT4,Claude AI,Gemini,Perplexity AI) 在母胎医学中的优势和局限性.
- 评估GAI在文献检索,指南比较和围产科手稿起草方面的实用性.
主要方法:
- 使用结构化临床提示来模拟GAI工具的现实应用.
- 与传统方法相比,基于引用准确性,内容总结和时间效率来评估性能.
主要成果:
- 困惑的人工智能显示出优越的引用准确性;ChatGPT4和Claude AI在总结方面表现出色,但需要手动引用检查.
- 与PubMed搜索相比,GAI工具将总结生成时间减少了高达70%.
- 确定的风险包括幻觉引用和潜在的过度依赖人工智能产生的内容.
结论:
- GAI工具可以通过协助文献审查和指导方针合成,显著提高围产科的效率.
- 负责任的整合要求临床医生培养人工智能素养,保持关键监督,并遵守道德标准.
- GAI应该作为一个支持工具,而不是替代产周护理专家临床判断.
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