Machine Learning and Omics Analysis in Aortic Aneurysm.

IF 2.6 3区 医学 Q2 PERIPHERAL VASCULAR DISEASE
Angiology Pub Date : 2024-11-01 Epub Date: 2023-10-10 DOI:10.1177/00033197231206427
Fabien Lareyre, Arindam Chaudhuri, Bahaa Nasr, Juliette Raffort
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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.

主动脉瘤的机器学习和Omics分析。
主动脉瘤是一种危及生命的疾病,其形成和发展的机制尚不完全清楚。奥密克戎方法为识别广泛的生物标志物和更好地理解所涉及的细胞和分子途径带来了新的见解。Omics生成了大量数据,几项研究强调,人工智能(AI)和机器学习(ML)/深度学习(DL)等技术可以用于分析此类复杂的数据集。然而,到目前为止,只有少数研究报道了ML/DL用于主动脉瘤的组学分析。本研究的目的是总结使用ML/DL进行组学分析的最新进展,以解读主动脉瘤的病理生理学,并开发患者定制的风险预测模型。根据目前的知识,我们讨论了当前的局限性,并强调了该领域的未来方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Angiology
Angiology 医学-外周血管病
CiteScore
5.50
自引率
14.30%
发文量
180
审稿时长
6-12 weeks
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
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