Machine Learning and Omics Analysis in Aortic Aneurysm.

Journal: Angiology
Published Date:

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.

Authors

  • Fabien Lareyre
    Université Côte d'Azur, CHU, Inserm U1065, C3M, Nice, France; Department of Vascular Surgery, University Hospital of Nice, Nice, France.
  • Arindam Chaudhuri
    Bedfordshire-Milton Keynes Vascular Centre, Bedfordshire Hospitals NHS Foundation Trust, Bedford, UK.
  • Bahaa Nasr
    LaTIM, INSERM UMR1101, Brest, France.
  • Juliette Raffort
    Clinical Chemistry Laboratory, University Hospital of Nice, Nice, France; Université Côte d'Azur, CHU, Inserm U1065, C3M, Nice, France. Electronic address: juliette.raffort@hotmail.fr.