冠状病毒研究主题,追踪二十年的研究成果
Amir Aryani1, Jingbo Wang2, Luis Salvador-Carulla3
1Swinburne University of Technology, Melbourne, Australia. aaryani@swin.edu.au.
Scientific data
|June 10, 2025
概括
这项研究创建了超过80万篇冠状病毒 (CoV) 研究文章的综合数据集,使用自然语言处理跟踪COVID-19研究,疫苗开发和公共卫生战略的趋势.
科学领域:
- 病毒学 病毒学
- 公共卫生 公共卫生
- 数据科学数据科学数据科学
背景情况:
- 随着COVID-19的流行,大量的研究产生了巨大影响,需要系统的分析来了解其广泛的影响.
- 对冠状病毒 (CoV) 的持续研究需要工具来合成不断发展的知识.
- 对COVID-19的实时监测已经减少,但正在进行的研究涌入需要继续审查.
研究的目的:
- 开发一个管道系统地编目和综合全球Cov研究.
- 为未来的研究创建可重复使用的Cov研究文章数据集.
- 识别和组织冠状病毒领域的研究趋势和创新.
主要方法:
- 利用自然语言处理 (NLP) 技术开发了一个研究目录管道.
- 在2002年7月至2024年5月期间发表的超过80万篇研究文章的汇总和组织.
- 杆专家审查以确保数据集的准确性和相关性.
主要成果:
- 创建了全球冠状病毒研究的综合数据集.
- 对主题集群进行有组织的研究,包括疫苗开发,公共卫生,感染机制,心理健康和经济影响.
- 该数据集提供了研究趋势和创新的结构化概述.
结论:
- 开发的数据集和管道为研究冠状病毒和流行病的研究人员提供了宝贵的资源.
- 有助于更深入地了解大流行病的多方面的后果和潜在的未来研究方向.
- 提高Cov研究的可访问性和可重复使用性,以促进科学进步.
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