【摘要】 近年来，人工智能（AI）技术在肝病临床试验领域的探索与发展，推动了肝病临床试验的不断创新。AI已逐渐成为患者筛选、风险预测、终点评价及结果解读等临床试验环节的重要技术工具。然而，AI在临床试验中的规范化应用仍面临数据质控、模型可解释性及因果推断等方面的方法学挑战。本文基于方法学视角，针对AI作为研究对象（验证型）和AI作为研究工具（辅助型）两类临床试验，系统梳理其在肝病领域的主要应用场景，探讨相关方法学挑战及解决策略，旨在为促进该技术的规范化应用提供方法学参考。更多还原

【Abstract】 In recent years, the exploration and development of artificial intelligence(AI) technology in clinical trials for liver diseases have promoted the continuous innovation of research methods and processes in this field. AI has gradually become an important technical tool for various links of clinical trial including patient selection, risk stratification, endpoint evaluation, and result interpretation. Nevertheless, the standardized integration of AI into clinical trials still faces the methodological challenges such as data quality control, model interpretability, and causal inference. From the perspective of methodology, this article systematically reviews the principal application scenarios of AI as an object under investigation(validation trials) and as a research tool(supportive trials) in clinical trials for liver diseases, as well as the major methodological challenges of AI-related clinical trials along and the corresponding solution strategies, in order to provide methodological guidance for promoting the scientific and standardized implementation of AI technologies.更多还原