PDF(Pubmed)
Abstract：
Systematic reviews are a cornerstone for synthesizing the available evidence on a given topic. They simultaneously allow for gaps in the literature to be identified and provide direction for future research. However, due to the ever-increasing volume and complexity of the available literature, traditional methods for conducting systematic reviews are less efficient and more time-consuming. Numerous artificial intelligence (AI) tools are being released with the potential to optimize efficiency in academic writing and assist with various stages of the systematic review process including developing and refining search strategies, screening titles and abstracts for inclusion or exclusion criteria, extracting essential data from studies and summarizing findings. Therefore, in this article we provide an overview of the currently available tools and how they can be incorporated into the systematic review process to improve efficiency and quality of research synthesis. We emphasize that authors must report all AI tools that have been used at each stage to ensure replicability as part of reporting in methods.
摘要：
系统评价是综合给定主题的现有证据的基石。它们同时允许确定文献中的空白，并为未来的研究提供方向。然而,由于现有文献的数量和复杂性不断增加，进行系统评价的传统方法效率较低，耗时较多。许多人工智能（AI）工具正在发布，有可能优化学术写作效率，并协助系统审查过程的各个阶段，包括开发和完善搜索策略。筛选标题和摘要的纳入或排除标准，从研究中提取基本数据并总结发现。因此,在本文中，我们概述了当前可用的工具，以及如何将它们纳入系统综述过程，以提高研究综合的效率和质量。我们强调，作者必须报告每个阶段使用的所有AI工具，以确保可复制性，作为方法报告的一部分。
