Machine Learning and Omics Analysis in Aortic Aneurysm.
abdominal aortic aneurysm
aortic aneurysm
artificial intelligence
biomarkers
deep learning
machine learning
omics
thoracic aortic aneurysm
Journal
Angiology
ISSN: 1940-1574
Titre abrégé: Angiology
Pays: United States
ID NLM: 0203706
Informations de publication
Date de publication:
10 Oct 2023
10 Oct 2023
Historique:
medline:
11
10
2023
pubmed:
11
10
2023
entrez:
11
10
2023
Statut:
aheadofprint
Résumé
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.
Identifiants
pubmed: 37817423
doi: 10.1177/00033197231206427
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
33197231206427Déclaration de conflit d'intérêts
Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.