Fabien Lareyre , Arindam Chaudhuri , Christian-Alexander Behrendt , Alexandre Pouhin , Martin Teraa , Jonathan R. Boyle , Riikka Tulamo , Juliette Raffort
{"title":"Artificial intelligence–based predictive models in vascular diseases","authors":"Fabien Lareyre , Arindam Chaudhuri , Christian-Alexander Behrendt , Alexandre Pouhin , Martin Teraa , Jonathan R. Boyle , Riikka Tulamo , Juliette Raffort","doi":"10.1053/j.semvascsurg.2023.05.002","DOIUrl":null,"url":null,"abstract":"<div><p><span><span>Cardiovascular disease represents a source of major health problems worldwide, and although medical and technical advances have been achieved, they are still associated with high morbidity and mortality rates. Personalized medicine would benefit from novel tools to better predict individual prognosis and outcomes after intervention. Artificial intelligence (AI) has brought new insights to </span>cardiovascular medicine, especially with the use of machine learning techniques that allow the identification of hidden patterns and complex associations in health data without any </span><em>a priori</em><span> assumptions. This review provides an overview on the use of artificial intelligence–based prediction models in vascular diseases, specifically focusing on aortic aneurysm<span>, lower extremity arterial disease<span><span>, and carotid stenosis. Potential benefits include the development of precision medicine </span>in patients with vascular diseases. In addition, the main challenges that remain to be overcome to integrate artificial intelligence–based predictive models in clinical practice are discussed.</span></span></span></p></div>","PeriodicalId":51153,"journal":{"name":"Seminars in Vascular Surgery","volume":"36 3","pages":"Pages 440-447"},"PeriodicalIF":3.3000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Seminars in Vascular Surgery","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0895796723000388","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PERIPHERAL VASCULAR DISEASE","Score":null,"Total":0}
引用次数: 0
Abstract
Cardiovascular disease represents a source of major health problems worldwide, and although medical and technical advances have been achieved, they are still associated with high morbidity and mortality rates. Personalized medicine would benefit from novel tools to better predict individual prognosis and outcomes after intervention. Artificial intelligence (AI) has brought new insights to cardiovascular medicine, especially with the use of machine learning techniques that allow the identification of hidden patterns and complex associations in health data without any a priori assumptions. This review provides an overview on the use of artificial intelligence–based prediction models in vascular diseases, specifically focusing on aortic aneurysm, lower extremity arterial disease, and carotid stenosis. Potential benefits include the development of precision medicine in patients with vascular diseases. In addition, the main challenges that remain to be overcome to integrate artificial intelligence–based predictive models in clinical practice are discussed.
期刊介绍:
Each issue of Seminars in Vascular Surgery examines the latest thinking on a particular clinical problem and features new diagnostic and operative techniques. The journal allows practitioners to expand their capabilities and to keep pace with the most rapidly evolving areas of surgery.