A physiologically realistic virtual patient database for the study of arterial haemodynamics-Reference-Cited by-同舟云学术

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A physiologically realistic virtual patient database for the study of arterial haemodynamics

Published:2021-05-31 Issue:10 Volume:37 Page:
ISSN:2040-7939
Container-title:International Journal for Numerical Methods in Biomedical Engineering
language:en
Short-container-title:Int J Numer Meth Biomed Engng

Author:

Jones Gareth¹,Parr Jim²,Nithiarasu Perumal¹,Pant Sanjay¹^ORCID

Affiliation:

1. College of Engineering Swansea University Swansea UK

2. Applied Technologies McLaren Technology Centre Woking UK

Funder

Engineering and Physical Sciences Research Council

Publisher

Wiley

Subject

Applied Mathematics,Computational Theory and Mathematics,Molecular Biology,Modelling and Simulation,Biomedical Engineering,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cnm.3497

Reference81 articles.

1. Comparison of global estimates of prevalence and risk factors for peripheral artery disease in 2000 and 2010: a systematic review and analysis

2. Subclavian Artery Stenosis: Prevalence, Risk Factors, and Association With Cardiovascular Diseases

3. Prevalence of and Risk Factors Associated with Carotid Artery Stenosis: The Tromsø Study

4. Prevalence and Trends of the Abdominal Aortic Aneurysms Epidemic in General Population - A Meta-Analysis

5. Twenty-year review of abdominal aortic aneurysm screening in men in the county of Gloucestershire, United Kingdom

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1. An in silico study of the effects of cardiovascular aging on carotid flow waveforms and indexes in a virtual population;American Journal of Physiology-Heart and Circulatory Physiology;2024-04-01

2. Hemodynamics of vascular shunts: trends, challenges, and prospects;Biophysical Reviews;2023-10

3. First blood: An efficient, hybrid one‐ and zero‐dimensional, modular hemodynamic solver;International Journal for Numerical Methods in Biomedical Engineering;2023-03-22

4. Computational Analysis of Hemodynamic Indices Based on Personalized Identification of Aortic Pulse Wave Velocity by a Neural Network;Mathematics;2023-03-10

5. Classification and regression of stenosis using an in-vitro pulse wave data set: Dependence on heart rate, waveform and location;Computers in Biology and Medicine;2022-12

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