关键词: 胆管癌, 影像组学, 鉴别诊断, 人工智能, 深度学习, 精准医疗

Abstract: Artificial intelligence (AI) has demonstrated significant potential in the diagnosis and treatment of cholangiocarcinoma. Deep learning-based imaging analysis techniques enable automated lesion segmentation, accurate differential diagnosis, and prediction of pathological behaviors such as lymph node metastasis, substantially improving diagnostic efficacy. Endoscopic assistance systems, utilizing convolutional neural networks, facilitate real-time identification of biliary structures and malignant strictures, optimizing procedural workflows. In pathological diagnosis, AI models leverage hyperspectral or conventional white-light pathological scanned images to achieve tumor classification and molecular subtyping, providing critical support for prognostic assessment and targeted therapy. Current challenges primarily include insufficient data standardization and limited model generalizability. Future advancements will require multicenter collaboration and algorithmic optimization to promote clinical translation. 

Key words: cholangiocarcinoma, radiomics, differential diagnosis, artificial intelligence, deep learning, precision medicine