Department of Philosophy, School of the Art, University of Liverpool, Liverpool L69 3BX, United Kingdom.
Department of Philosophy, School of Humanities, Central South University, Changsha, Hunan 410075, P.R. China.
J Am Med Inform Assoc. 2024 Nov 1;31(11):2749-2759. doi: 10.1093/jamia/ocae243.
The objective of our research is to conduct a comprehensive review that aims to systematically map, describe, and summarize the current utilization of artificial intelligence (AI) in the recruitment and retention of participants in clinical trials.
A comprehensive electronic search was conducted using the search strategy developed by the authors. The search encompassed research published in English, without any time limitations, which utilizes AI in the recruitment process of clinical trials. Data extraction was performed using a data charting table, which included publication details, study design, and specific outcomes/results.
The search yielded 5731 articles, of which 51 were included. All the studies were designed specifically for optimizing recruitment in clinical trials and were published between 2004 and 2023. Oncology was the most covered clinical area. Applying AI to recruitment in clinical trials has demonstrated several positive outcomes, such as increasing efficiency, cost savings, improving recruitment, accuracy, patient satisfaction, and creating user-friendly interfaces. It also raises various technical and ethical issues, such as limited quantity and quality of sample size, privacy, data security, transparency, discrimination, and selection bias.
While AI holds promise for optimizing recruitment in clinical trials, its effectiveness requires further validation. Future research should focus on using valid and standardized outcome measures, methodologically improving the rigor of the research carried out.
我们的研究目的是进行全面综述，旨在系统地描绘、描述和总结当前人工智能（AI）在临床试验参与者招募和保留中的应用。
作者制定了全面的电子搜索策略，对发表于英文期刊、无时间限制、利用 AI 进行临床试验招募过程的研究进行了搜索。使用数据图表表格进行数据提取，其中包括出版物详细信息、研究设计和具体的结果/发现。
搜索共产生 5731 篇文章，其中 51 篇被纳入。所有研究都是专门为优化临床试验的招募而设计的，发表时间在 2004 年至 2023 年之间。肿瘤学是最受关注的临床领域。在临床试验的招募中应用 AI 已显示出多种积极结果，例如提高效率、节省成本、改善招募、准确性、患者满意度和创建用户友好的界面。它还引发了各种技术和伦理问题，例如样本量和质量有限、隐私、数据安全、透明度、歧视和选择偏差。
虽然 AI 有希望优化临床试验的招募，但它的有效性需要进一步验证。未来的研究应侧重于使用有效和标准化的结果测量方法，从方法学上提高所开展研究的严谨性。
