破译
组学
医学
主动脉瘤
动脉瘤
计算生物学
生物信息学
人工智能
机器学习
数据科学
计算机科学
生物
放射科
作者
Fabien Lareyre,Arindam Chaudhuri,Bahaa Nasr,Juliette Raffort
标识
DOI:10.1177/00033197231206427
摘要
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.
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