【摘要】 肝细胞癌（HCC）是全球最常见的恶性肿瘤之一，其预后评估和治疗策略的制定对改善患者生存至关重要。传统预后模型依赖有限的临床病理参数，难以全面反映肿瘤的高度异质性。近年来，人工智能（AI）技术，特别是机器学习和深度学习，凭借强大的数据挖掘与模式识别能力，推动了HCC精准诊疗的变革。本文系统总结了AI在HCC预后评估与治疗优化中的最新进展，重点阐述影像组学、多模态数据融合等关键方法，探讨其在术后复发预测、疗效评估及个体化治疗决策中的应用潜力与挑战，并展望AI未来的发展方向，旨在为加速AI技术在HCC临床转化中的应用提供参考。更多还原

【Abstract】 Hepatocellular carcinoma(HCC) is one of the most prevalent malignancies worldwide, and accurate prognostic assessment and treatment planning are vital for improving patient outcomes. Conventional prognostic models, which rely on limited clinicopathological parameters, often fail to capture the profound heterogeneity of HCC. In recent years, artificial intelligence(AI)-particularly machine learning and deep learning-has driven a paradigm shift in precision oncology by leveraging its powerful capabilities in data mining and pattern recognition. This review provides a comprehensive overview of recent advances in AI for prognostic assessment and treatment optimization in HCC, with an emphasis on key methodologies such as radiomics and multi-modal data integration. It further discusses the clinical potential and challenges of AI in predicting postoperative recurrence, evaluating therapeutic response, and supporting individualized treatment decisions, while also outlining future directions in this rapidly evolving field. The review aims to inform and facilitate the clinical translation of AI technologies into the management of HCC.更多还原