{"title":"Artificial Intelligence and Machine Learning for Risk Prediction of Abdominal Aortic Aneurysm Growth and Rupture.","authors":"Jia Guo, Fabien Lareyre, Regent Lee, Martin Teraa, Hervé Delingette, Juliette Raffort","doi":"10.1177/00033197251379127","DOIUrl":null,"url":null,"abstract":"<p><p>Artificial intelligence (AI) and machine learning (ML) are emerging tools in the management of abdominal aortic aneurysms (AAA). They have offered new tools to develop advanced imaging analysis and prediction models. This narrative review summarizes studies exploring AI/ML models to evaluate the risk of AAA growth and rupture. We provide an overview and critical analysis on methodology used, identify current limits and propose future directions for research and implementation in surgical practice.</p>","PeriodicalId":8264,"journal":{"name":"Angiology","volume":" ","pages":"1091-1097"},"PeriodicalIF":2.7000,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Angiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/00033197251379127","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/10/21 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"PERIPHERAL VASCULAR DISEASE","Score":null,"Total":0}
引用次数: 0
Abstract
Artificial intelligence (AI) and machine learning (ML) are emerging tools in the management of abdominal aortic aneurysms (AAA). They have offered new tools to develop advanced imaging analysis and prediction models. This narrative review summarizes studies exploring AI/ML models to evaluate the risk of AAA growth and rupture. We provide an overview and critical analysis on methodology used, identify current limits and propose future directions for research and implementation in surgical practice.
期刊介绍:
A presentation of original, peer-reviewed original articles, review and case reports relative to all phases of all vascular diseases, Angiology (ANG) offers more than a typical cardiology journal. With approximately 1000 pages per year covering diagnostic methods, therapeutic approaches, and clinical and laboratory research, ANG is among the most informative publications in the field of peripheral vascular and cardiovascular diseases. This journal is a member of the Committee on Publication Ethics (COPE). Average time from submission to first decision: 13 days