In recent years, artificial intelligence (AI) has made significant progress in the management of aortic dilatation diseases, including aortic dissection and aortic aneurysm, with applications spanning intelligent diagnosis, treatment decision support, and postoperative management. AI technologies, leveraging imaging analysis, multimodal data fusion, intelligent surgical assistance, and prognostic modeling, have improved early screening efficiency, personalized treatment precision, and long-term monitoring outcomes. However, current AI models face challenges such as poor interpretability, lack of standardized training data, and limited multicenter validation. Future efforts should focus on data sharing, the establishment of unified standards, and interdisciplinary collaboration to promote broader clinical adoption of AI in aortic dilatation diseases.
近年来，人工智能在主动脉扩张性疾病领域的应用取得了显著进展，覆盖了主动脉夹层和主动脉瘤的智能诊断、治疗决策支持及术后管理等多个环节。借助影像学分析、多模态数据融合、智能手术辅助及预后预测等技术手段，人工智能提升了疾病的早期筛查效率、个性化治疗的精准度及长期随访监测的效果。然而，当前人工智能模型仍面临可解释性不足、训练数据标准化程度不高、多中心验证研究缺乏等挑战。未来需进一步推动数据共享、制订统一的技术规范，加快人工智能技术在主动脉扩张性疾病中的临床应用。.