School of Humanities, Central South University, Changsha, People's Republic of China.
University of Liverpool Faculty of Arts, Liverpool, UK.
BMJ Open. 2024 Mar 19;14(3):e080032. doi: 10.1136/bmjopen-2023-080032.
In recent years, the influence of artificial intelligence technology on clinical trials has been steadily increasing. It has brought about significant improvements in the efficiency and cost reduction of clinical trials. The objective of this scoping review is to systematically map, describe and summarise the current utilisation of artificial intelligence in recruitment and retention process of clinical trials that has been reported in research. Additionally, the review aims to identify benefits and drawbacks, as well as barriers and facilitators associated with the application of artificial intelligence in optimising recruitment and retention in clinical trials. The findings of this review will provide insights and recommendations for future development of artificial intelligence in the context of clinical trials.
The review of relevant literature will follow the methodological framework for scoping studies provided by the Joanna Briggs Institute. A comprehensive electronic search will be conducted using the search strategy developed by the authors. Leading medical and computer science databases such as PubMed, Embase, Scopus, IEEE Xplore and Web of Science Core Collection will be searched. The search will encompass analytical observational studies, descriptive observational studies, experimental and quasi-experimental studies published in all languages, without any time limitations, which use artificial intelligence tools in the recruitment and retention process of clinical trials. The review team will screen the identified studies and import them into a dedicated electronic library specifically created for this review. Data extraction will be performed using a data charting table.
Secondary data will be attained in this scoping review; therefore, no ethical approval is required. The results of the final review will be published in a peer-reviewed journal. It is expected that results will inform future artificial intelligence and clinical trials research.
近年来，人工智能技术对临床试验的影响稳步增加。它提高了临床试验的效率和降低了成本。本范围综述的目的是系统地绘制、描述和总结目前在研究中报告的人工智能在临床试验招募和保留过程中的应用情况。此外，该综述旨在确定人工智能在优化临床试验招募和保留方面的应用的优缺点、障碍和促进因素。本综述的结果将为未来临床试验中人工智能的发展提供见解和建议。
对相关文献的综述将遵循由 Joanna Briggs 研究所提供的范围研究方法框架。作者将制定全面的电子搜索策略，利用 PubMed、Embase、Scopus、IEEE Xplore 和 Web of Science Core Collection 等主要医学和计算机科学数据库进行搜索。搜索将包括在临床试验的招募和保留过程中使用人工智能工具的分析观察性研究、描述性观察性研究、实验和准实验研究，涵盖所有语言，没有任何时间限制。综述团队将筛选确定的研究，并将其导入专为本次综述创建的专用电子文库。将使用数据图表表进行数据提取。
本次范围综述将使用二次数据，因此不需要伦理批准。最终综述的结果将发表在同行评审的期刊上。预计结果将为未来的人工智能和临床试验研究提供信息。
