在临床试验风险评估中对人工智能应用的范围审查
Douglas Teodoro1, Nona Naderi2, Anthony Yazdani3
1Department of Radiology and Medical Informatics, Faculty of Medicine, University of Geneva, Geneva, Switzerland. douglas.teodoro@unige.ch.
NPJ digital medicine
|July 29, 2025
概括
人工智能 (AI) 增强了临床试验安全性和效率的风险评估. 人工智能模型看起来很有前途,但需要解决数据质量等挑战,以便更广泛地采用.
科学领域:
- 临床研究 临床研究
- 人工智能的人工智能
- 风险管理 风险管理
背景情况:
- 人工智能 (AI) 越来越多地被用于临床试验风险评估,以提高安全性和运营效率.
- 越来越多的研究正在探索AI应用,用于预测临床试验中的安全性,有效性和运营风险.
研究的目的:
- 对应用人工智能的临床试验风险评估研究进行范围审查.
- 识别人工智能技术,数据源和安全,有效性和运营风险预测中的应用.
- 评估AI驱动的临床试验风险评估的性能和挑战.
主要方法:
- 在2013年至2024年间发表的142项研究的系统搜索和分析.
- 基于风险预测重点的研究分类:安全性 (55),有效性 (46) 和操作性 (45).
- 识别和合成人工智能方法 (机器学习,深度学习,LLM) 和使用的数据源.
主要成果:
- 人工智能技术,包括传统的ML,深度学习和因果ML,用于预测不良事件,治疗效应和试验阶段过渡.
- 利用多种数据来源,从分子数据和协议到患者信息和出版物.
- 大型语言模型 (LLM) 显示了最近应用的激增,在2023年33项研究中的7项中出现,报告的性能高达96%AUROC.
结论:
- 基于人工智能的风险评估显示了提高临床试验安全性和效率的巨大潜力.
- 解决诸如选择偏见,有限的前景验证和数据质量等挑战对于实现人工智能的全部影响至关重要.
- 人工智能有望改变临床试验,特别是在开发基于风险的高级监测框架方面.
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