Artificial intelligence-based predictive models in vascular diseases.

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

Journal

Seminars in vascular surgery
ISSN: 1558-4518
Titre abrégé: Semin Vasc Surg
Pays: United States
ID NLM: 8809602

Informations de publication

Date de publication:
Sep 2023
Historique:
received: 02 12 2022
revised: 24 04 2023
accepted: 24 05 2023
medline: 31 10 2023
pubmed: 21 10 2023
entrez: 20 10 2023
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 37863618
pii: S0895-7967(23)00038-8
doi: 10.1053/j.semvascsurg.2023.05.002
pii:
doi:

Substances chimiques

Cardiovascular Agents 0

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

440-447

Informations de copyright

Copyright © 2023 Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare no competing interest

Auteurs

Fabien Lareyre (F)

Department of Vascular Surgery, Hospital of Antibes Juan-les-Pins, France; Université Côte d'Azur, INSERM U1065, C3M, Nice, France.

Arindam Chaudhuri (A)

Bedfordshire-Milton Keynes Vascular Centre, Bedfordshire Hospitals NHS Foundation Trust, Bedford, UK.

Christian-Alexander Behrendt (CA)

Brandenburg Medical School Theodor-Fontane, Neuruppin, Germany; Department of Vascular and Endovascular Surgery, Asklepios Medical School Hamburg, Asklepios Clinic Wandsbek, Hamburg, Germany.

Alexandre Pouhin (A)

Division of Vascular Surgery, Dijon University Hospital, Dijon, France.

Martin Teraa (M)

Department of Vascular Surgery, University Medical Center Utrecht, Utrecht, The Netherlands.

Jonathan R Boyle (JR)

Cambridge Vascular Unit, Cambridge University Hospitals NHS Trust and Department of Surgery, University of Cambridge, Cambridge, UK.

Riikka Tulamo (R)

Department of Vascular Surgery, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.

Juliette Raffort (J)

Université Côte d'Azur, INSERM U1065, C3M, Nice, France; Institute 3IA Côte d'Azur, Université Côte d'Azur, France; Clinical Chemistry Laboratory, University Hospital of Nice, France. Electronic address: raffort-lareyre.j@chu-nice.fr.

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Classifications MeSH