使用Bing的人工智能搜索引擎用于数据提取的方法,以进行系统审查
James Edward Hill1, Catherine Harris1, Andrew Clegg1
1Synthesis, Economic Evaluation and Decision Science (SEEDS) Group, University of Central Lancashire, Preston, UK.
Research synthesis methods
|December 9, 2023
概括
这项研究探讨了使用Bing AI作为系统审查中的数据提取的第二个审查员. 人工智能可以帮助人类审稿人,节省时间和资源,但在取代传统方法之前需要进一步验证.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 系统审查方法论 系统审查方法论
背景情况:
- 在系统性审查中提取数据是劳动密集型的.
- 自然语言处理 (NLP) 和人工智能 (AI) 提供了自动化潜力.
- 提高系统审查的效率和可靠性至关重要.
研究的目的:
- 提出并演示使用Bing AI作为数据提取的二级审核器的方法.
- 评估AI在验证和增强人类审查员提取的数据方面的潜力.
- 为资源有限的系统审查提供一个具有成本效益的解决方案.
主要方法:
- 一个工作示例详细介绍了使用Bing AI Chat从PDF文档中提取研究特征.
- 指导人工智能将数据填充到表格中,以与人类提取的数据进行比较.
- 使用微软Edge作为人工智能辅助验证的平台.
主要成果:
- 可以指示Bing AI从文档中提取特定数据项.
- 人工智能辅助方法为数据提取提供了一个额外的验证层.
- 这种方法对于资源或经验有限的审稿人来说可能是有益的.
结论:
- 在系统性审查中,Bing AI显示出作为数据提取的补充工具的前景.
- 它可以加强验证流程,特别是当资源稀缺时.
- 需要进一步的研究来验证AI的准确性和效率与既有双提取方法相比.
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