Published September 2023
| Version v1
Journal article
Artificial intelligence in vascular surgical decision making
Contributors
Others:
- Department of Vascular Surgery, Hospital of Antibes Juan-les-Pins, Antibes, France ; Hospital of Antibes Juan-les-Pins
- Centre méditerranéen de médecine moléculaire (C3M) ; Université Nice Sophia Antipolis (1965 - 2019) (UNS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Côte d'Azur (UCA)
- Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Department of Surgery, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands ; Vrije Universiteit Amsterdam [Amsterdam] (VU)
- Interdisciplinary Institute for Artificial Intelligence (3iA Côte d'Azur)
- E-Patient : Images, données & mOdèles pour la médeciNe numériquE (EPIONE) ; Inria Sophia Antipolis - Méditerranée (CRISAM) ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)
- Department of Vascular Surgery, Hospital of Antibes Juan-les-Pins, Antibes, France ; Hospital of Antibes Juan-les-Pin
- Bedfordshire-Milton Keynes Vascular Centre, Bedfordshire Hospitals NHS Foundation Trust, Bedford, UK ; Bedfordshire Hospitals NHS Foundation Trust
- Brandenburg Medical School Theodor Fontane & Health Services Research Witten [Neuruppin, Germany] ; Universität Witten - Herdecke [Germany]
- Department of Vascular and Endovascular Surgery, Asklepios Medical School Hamburg, Asklepios Clinic Wandsbek, Hamburg, Germany ; Asklepios Medical School Hamburg
- Department of Vascular Surgery, School of Health Sciences, Faculty of Medicine, University Hospital of Larissa, University of Thessaly, Larissa, Greece ; University of Thessaly [Larissa]
- Laboratoire de chimie clinique ; Centre Hospitalier Universitaire de Nice (CHU Nice)
- ANR-22-CE45-0023,PREDICTA,Création d'un système de support d'aide à la décision thérapeutique pour la prise en charge des anévrismes de l'aorte(2022)
- ANR-19-P3IA-0002,3IA@cote d'azur,3IA Côte d'Azur(2019)
Description
Despite advances in prevention, detection, and treatment, cardiovascular disease is a leading cause of mortality and represents a major health problem worldwide. Artificial intelligence and machine learning have brought new insights to the management of vascular diseases by allowing analysis of huge and complex datasets and by offering new techniques to develop advanced imaging analysis. Artificial intelligence–based applications have the potential to improve prognostic evaluation and evidence-based decision making and contribute to vascular therapeutic decision making. In this scoping review, we provide an overview on how artificial intelligence could help in vascular surgical clinical decision making, highlighting potential benefits, current limitations, and future challenges.
Abstract
International audienceAdditional details
Identifiers
- URL
- https://inria.hal.science/hal-04361618
- URN
- urn:oai:HAL:hal-04361618v1
Origin repository
- Origin repository
- UNICA