摘要神经内分泌肿瘤(NEN)异质性强，传统影像与病理评估难以满足个体化需求。本文系统综述人工智能结合影像组学、病理组学及多模态融合模型在NEN中的应用进展。总结人工智能在NEN鉴别、分级、转移、预后及疗效预测等方面的表现。多模态人工智能模型能显著提升评估准确性。然而，现有研究多为回顾性设计，临床转化仍面临挑战。未来，亟需构建标准化数据库、开发可解释算法，并开展前瞻性多中心验证，以推动人工智能临床落地。

abstractsNeuroendocrine neoplasms (NENs) are highly heterogeneous, and traditional imaging and pathological evaluations are often inadequate for personalized management. This article systematically reviews the application of artificial intelligence (AI) combined with radiomics, pathomics, and multimodal fusion models in NENs. It summarizes the performance of AI in the differentiation, grading, metastasis, prognosis, and therapeutic response prediction of NENs. Multimodal AI models can significantly improve the accuracy of assessment. However, most existing studies are retrospective in design, and clinical translation still faces challenges. In the future, it is imperative to establish standardized databases, develop interpretable algorithms, and conduct prospective multicenter validations to promote the clinical application of AI.