How to optimize the systematic review process using AI tools

JCPP advances Pub Date : 2024-04-23 DOI:10.1002/jcv2.12234
Nicholas Fabiano, Arnav Gupta, Nishaant Bhambra, Brandon Luu, Stanley Wong, Muhammad Maaz, Jess G. Fiedorowicz, Andrew L. Smith, Marco Solmi
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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.

如何利用人工智能工具优化系统性审查流程
系统综述是综合特定主题现有证据的基石。同时,系统综述还能发现文献中的不足,为未来研究提供方向。然而,由于现有文献的数量和复杂性不断增加,进行系统综述的传统方法效率较低且耗时较长。大量人工智能(AI)工具的发布有可能优化学术写作的效率,并在系统综述过程的各个阶段提供帮助,包括制定和完善检索策略、根据纳入或排除标准筛选标题和摘要、从研究中提取重要数据以及总结研究结果。因此,我们在本文中概述了当前可用的工具,以及如何将这些工具纳入系统综述流程,以提高研究综述的效率和质量。我们强调,作为方法报告的一部分,作者必须报告每个阶段使用的所有人工智能工具,以确保可复制性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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