{"title":"Machine Learning and Omics Analysis in Aortic Aneurysm.","authors":"Fabien Lareyre, Arindam Chaudhuri, Bahaa Nasr, Juliette Raffort","doi":"10.1177/00033197231206427","DOIUrl":null,"url":null,"abstract":"<p><p>Aortic aneurysm is a life-threatening condition and mechanisms underlying its formation and progression are still incompletely understood. Omics approach has brought new insights to identify a broad spectrum of biomarkers and better understand cellular and molecular pathways involved. Omics generate a large amount of data and several studies have highlighted that artificial intelligence (AI) and techniques such as machine learning (ML)/deep learning (DL) can be of use in analyzing such complex datasets. However, only a few studies have so far reported the use of ML/DL for omics analysis in aortic aneurysms. The aim of this study is to summarize recent advances on the use of ML/DL for omics analysis to decipher aortic aneurysm pathophysiology and develop patient-tailored risk prediction models. In the light of current knowledge, we discuss current limits and highlight future directions in the field.</p>","PeriodicalId":8264,"journal":{"name":"Angiology","volume":" ","pages":"921-927"},"PeriodicalIF":2.6000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Angiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/00033197231206427","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/10/10 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"PERIPHERAL VASCULAR DISEASE","Score":null,"Total":0}
引用次数: 0
Abstract
Aortic aneurysm is a life-threatening condition and mechanisms underlying its formation and progression are still incompletely understood. Omics approach has brought new insights to identify a broad spectrum of biomarkers and better understand cellular and molecular pathways involved. Omics generate a large amount of data and several studies have highlighted that artificial intelligence (AI) and techniques such as machine learning (ML)/deep learning (DL) can be of use in analyzing such complex datasets. However, only a few studies have so far reported the use of ML/DL for omics analysis in aortic aneurysms. The aim of this study is to summarize recent advances on the use of ML/DL for omics analysis to decipher aortic aneurysm pathophysiology and develop patient-tailored risk prediction models. In the light of current knowledge, we discuss current limits and highlight future directions in the field.
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