ArticleEuropean heart journal. Digital health2021
Leveraging the potential of machine learning for assessing vascular ageing: state-of-the-art and future research.
Article in European heart journal. Digital health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Machine learning assessment of retinal blood flow links metabolic dysfunction and accelerated microvascular aging.Scientific reports · 2026Article
- Digital hypertension - what we need for the high-quality management of hypertension in the new era.Hypertension research : official journal of the Japanese Society of Hypertension · 2025Review
- Overnight stiffness index from finger photoplethysmography in relation to markers of cardiovascular risk and vascular ageing.Heart and vessels · 2025Article
- Age group classification based on optical measurement of brain pulsation using machine learning.Scientific reports · 2025Article
- Testing an inverse modeling approach with gradient boosting regression for stroke volume estimation using patient thermodilution data.Frontiers in artificial intelligence · 2025Article
- Developing technologies to assess vascular ageing: a roadmap from VascAgeNet.Physiological measurement · 2024Review
- Development of a recommendation system and data analysis in personalized medicine: an approach towards healthy vascular ageing.Health information science and systems · 2024Article
- Validation of an early vascular aging construct model for comprehensive cardiovascular risk assessment using external risk indicators for improved clinical utility: data from the EVasCu study.Cardiovascular diabetology · 2024Article
- Estimation of aortic stiffness by finger photoplethysmography using enhanced pulse wave analysis and machine learning.Frontiers in cardiovascular medicine · 2024Article
- 2024 Recommendations for Validation of Noninvasive Arterial Pulse Wave Velocity Measurement Devices.Hypertension (Dallas, Tex. : 1979) · 2024Article
- Reimagining the Value of Brachial-Ankle Pulse Wave Velocity as a Biomarker of Cardiovascular Disease Risk-A Call to Action on Behalf of VascAgeNet.Hypertension (Dallas, Tex. : 1979) · 2023Review
- Heart Failure: Insights From the Arterial Waves.Journal of the American Heart Association · 2023Article
- Expert Consensus on the Clinical Use of Pulse Wave Velocity in Asia.Pulse (Basel, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Vascular ageing biomarkers have been found to be predictive of cardiovascular risk independently of classical risk factors, yet are not widely used in clinical practice. In this review, we present two basic approaches for using machine learning (ML) to assess vascular age: parameter estimation and risk classification. We then summarize their role in developing new techniques to assess vascular ageing quickly and accurately. We discuss the methods used to validate ML-based markers, the evidence for their clinical utility, and key directions for future research. The review is complemented by case studies of the use of ML in vascular age assessment which can be replicated using freely available data and code.
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