Artificial intelligence–based predictive models in vascular diseases

Fabien Lareyre, Arindam Chaudhuri, Christian Alexander Behrendt, Alexandre Pouhin, Martin Teraa, Jonathan R. Boyle, Riikka Tulamo, Juliette Raffort*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

1 Citation (Scopus)

Abstract

Cardiovascular disease represents a source of major health problems worldwide, and although medical and technical advances have been achieved, they are still associated with high morbidity and mortality rates. Personalized medicine would benefit from novel tools to better predict individual prognosis and outcomes after intervention. Artificial intelligence (AI) has brought new insights to cardiovascular medicine, especially with the use of machine learning techniques that allow the identification of hidden patterns and complex associations in health data without any a priori assumptions. This review provides an overview on the use of artificial intelligence–based prediction models in vascular diseases, specifically focusing on aortic aneurysm, lower extremity arterial disease, and carotid stenosis. Potential benefits include the development of precision medicine in patients with vascular diseases. In addition, the main challenges that remain to be overcome to integrate artificial intelligence–based predictive models in clinical practice are discussed.

Original languageEnglish
Pages (from-to)440-447
Number of pages8
JournalSeminars in Vascular Surgery
Volume36
Issue number3
DOIs
Publication statusPublished - Sept 2023

Keywords

  • Aortic disease
  • Artificial intelligence
  • Carotid stenosis
  • Lower extremity arterial disease
  • Machine learning
  • Peripheral artery disease
  • Predictive model
  • Vascular disease

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