Machine learning augmented reduced-order models for FFR-prediction

Effect of side branch flow upon physiological indices in coronary artery disease

(2020) Rebecca C. Gosling et al.   JOURNAL OF BIOMECHANICS

A Distributed Lumped Parameter Model of Blood Flow

(2020) Mehran Mirramezani et al.   ANNALS OF BIOMEDICAL ENGINEERING

Machine learning of multiscale active force generation models for the efficient simulation of cardiac electromechanics

(2020) F. Regazzoni et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

A zero-dimensional predictive model for the pressure drop in the stenotic coronary artery based on its geometric characteristics

(2020) Jaerim Kim et al.   JOURNAL OF BIOMECHANICS

Artificial Intelligence in Cardiovascular Imaging

(2019) Damini Dey et al.   JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY

Diagnostic accuracy of 3D deep-learning-based fully automated estimation of patient-level minimum fractional flow reserve from coronary computed tomography angiography

(2019) Kanako K Kumamaru et al.   European Heart Journal-Cardiovascular Imaging

A Cohort Longitudinal Study Identifies Morphology and Hemodynamics Predictors of Abdominal Aortic Aneurysm Growth

(2019) Florian Joly et al.   ANNALS OF BIOMEDICAL ENGINEERING

A feasibility study of deep learning for predicting hemodynamics of human thoracic aorta

(2019) Liang Liang et al.   JOURNAL OF BIOMECHANICS

Machine learning in cardiovascular flows modeling: Predicting arterial blood pressure from non-invasive 4D flow MRI data using physics-informed neural networks

(2019) Georgios Kissas et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Integrated prediction of lesion-specific ischaemia from quantitative coronary CT angiography using machine learning: a multicentre study

(2018) Damini Dey et al.   EUROPEAN RADIOLOGY

Deep learning analysis of the myocardium in coronary CT angiography for identification of patients with functionally significant coronary artery stenosis

(2018) Majd Zreik et al.   MEDICAL IMAGE ANALYSIS

Clinical Outcomes Using Coronary CT Angiography and FFRCT-Guided Management of Stable Chest Pain Patients

(2018) Bjarne L. Nørgaard et al.   JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY

Reduced Order Models for Transstenotic Pressure Drop in the Coronary Arteries

(2018) Mehran Mirramezani et al.   JOURNAL OF BIOMECHANICAL ENGINEERING-TRANSACTIONS OF THE ASME

Machine learning assessment of myocardial ischemia using angiography: Development and retrospective validation

(2018) Hyeonyong Hae et al.   PLOS MEDICINE

Uncertainty Quantification and Sensitivity Analysis for Computational FFR Estimation in Stable Coronary Artery Disease

(2018) Fredrik E. Fossan et al.   Cardiovascular Engineering and Technology

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

(2018) M. Raissi et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Estimating the accuracy of a reduced-order model for the calculation of fractional flow reserve (FFR)

(2017) Etienne Boileau et al.   International Journal for Numerical Methods in Biomedical Engineering

Artificial Intelligence in Precision Cardiovascular Medicine

(2017) Chayakrit Krittanawong et al.   JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY

Effect of stenosis eccentricity on the functionality of coronary bifurcation lesions—a numerical study

(2017) Catherine Pagiatakis et al.   MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING

Physiological Severity of Coronary Artery Stenosis Depends on the Amount of Myocardial Mass Subtended by the Coronary Artery

(2016) Hyung Yoon Kim et al.   JACC-Cardiovascular Interventions

A machine-learning approach for computation of fractional flow reserve from coronary computed tomography

(2016) Lucian Itu et al.   JOURNAL OF APPLIED PHYSIOLOGY

Impact of geometric uncertainty on hemodynamic simulations using machine learning

(2015) Sethuraman Sankaran et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Fast Computation of Hemodynamic Sensitivity to Lumen Segmentation Uncertainty

(2015) Sethuraman Sankaran et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Current Use of Fractional Flow Reserve: A Nationwide Survey

(2014) Bashar Hannawi et al.   TEXAS HEART INSTITUTE JOURNAL

Automatic segmentation, detection and quantification of coronary artery stenoses on CTA

(2013) Rahil Shahzad et al.   INTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING

Computational Fluid Dynamics Applied to Cardiac Computed Tomography for Noninvasive Quantification of Fractional Flow Reserve

(2013) Charles A. Taylor et al.   JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY

A validated predictive model of coronary fractional flow reserve

(2011) Y. Huo et al.   Journal of the Royal Society Interface

An image-based modeling framework for patient-specific computational hemodynamics

(2008) Luca Antiga et al.   MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING