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使用人工智能开发活体证据地图:药物制剂的例子
1Department of Oriental Neuropsychiatry, Dong-eui University College of Korean Medicine, 52-57, Yangjeong-ro, Busanjin-gu, Busan, Republic of Korea.
Integrative medicine research
|September 2, 2025
概括
一个人工智能 (AI) 系统自动创建和维护用于药物制剂研究的活证地图. 这种人工智能工具大大缩短了时间,提高了识别研究缺陷的准确性,使日常更新成为可能.
科学领域:
- 整合和补充医学
- 卫生信息学
- 研究中的人工智能
背景情况:
- 证据地图对于可视化研究景观和确定优先事项至关重要,但传统方法需要广泛的手册文献监测.
- 韩国的一种药物治疗方法是注射药物精液到针点, 这是一个越来越多的研究领域
- 需要有效的,最新的证据综合在药学等专业领域是显著的.
研究的目的:
- 开发和验证基于人工智能 (AI) 的自动化系统,用于构建和维护活的证据地图.
- 通过自动化系统,加强对药物制剂研究的缺口和优先事项的识别.
- 与手动方法相比,评估人工智能系统的性能和时间效率.
主要方法:
- 开发了一个基于网络的系统,集成PubMed API和Gemini AI用于自动化文献搜索,选择,数据提取和分类.
- 该系统的准确性在九个不同的任务中进行了评估,专家手动审查作为基准.
- 一个交互式泡图可视化系统被实施,以促进研究差距的直观识别.
主要成果:
- 在处理202篇文章时,人工智能系统表现出高的整体准确性 (94.00%),具体任务如样本大小提取实现了0%的错误.
- 大多数任务,包括药物取名称 (22.22%的错误率) 的准确度超过了90%.
- 时间效率显著提高,所需时间减少了68.9% (59分钟与190分钟相比),证实了每日更新的可行性.
结论:
- 人工智能驱动的活证据地图比静态的研究证据组织方法有了显著的改进.
- 该系统直观地识别了研究缺口,使未来的药物制剂研究能够更有效地确定优先级和方向.
- 开发的系统提供了准确的,持续更新的证据监测,为药研究节省了大量的时间和资源.
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