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.

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.