AIMC Topic: Models, Cardiovascular

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A comparative analysis of metamodels for 0D cardiovascular models, and pipeline for sensitivity analysis, parameter estimation, and uncertainty quantification.

Computers in biology and medicine Jul 1, 2025
Zero-dimensional (0D) cardiovascular models are reduced-order models aimed at studying the global dynamics of the whole circulation system or transport within it. They are employed to obtain estimates of important biomarkers for surgery planning and ...
Humans Neural Networks, Computer Models, Cardiovascular Uncertainty
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Towards fast and reliable estimations of 3D pressure, velocity and wall shear stress in aortic blood flow: CFD-based machine learning approach.

Computers in biology and medicine Jun 1, 2025
In this work, we developed deep neural networks for the fast and comprehensive estimation of the most salient features of aortic blood flow. These features include velocity magnitude and direction, 3D pressure, and wall shear stress. Starting from 40...
Humans Machine Learning Female Models, Cardiovascular Stress, Mechanical Adult Blood Flow Velocity Male Aorta Imaging, Three-Dimensional
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In Vitro Study of the Precision and Accuracy of Measurement of the Vascular Inner Diameter on Computed Tomography Angiography Using Deep Learning Image Reconstruction: Comparison With Filtered Back Projection and Iterative Reconstruction.

Journal of computer assisted tomography May 13, 2025
OBJECTIVE: This study aimed to compare the performance of deep learning image reconstruction (DLIR) with that of standard filtered back projection (FBP) and adaptive statistical iterative reconstruction V (ASiR-V) for measurement of the vascular diam...
Deep Learning Radiographic Image Interpretation, Computer-Assisted Phantoms, Imaging Computed Tomography Angiography Models, Cardiovascular Algorithms
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A Neural Network Finite Element Trileaflet Heart Valve Model Incorporating Multi-Body Contact.

International journal for numerical methods in biomedical engineering Apr 1, 2025
The use of patient-specific computational modeling of cardiovascular diseases has become increasingly popular to improve patient standard of care. Most simulation approaches currently utilize the finite element method (FEM), which is very well establ...
Humans Neural Networks, Computer Models, Cardiovascular Heart Valves Computer Simulation Finite Element Analysis
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ML-ROM wall shear stress prediction in patient-specific vascular pathologies under a limited clinical training data regime.

PloS one Jan 1, 2025
High-fidelity numerical simulations such as Computational Fluid Dynamics (CFD) have been proven effective in analysing haemodynamics, offering insight into many vascular conditions. However, these methods often face challenges of high computational c...
Computer Simulation Hemodynamics Peripheral Arterial Disease Stress, Mechanical Humans Neural Networks, Computer Machine Learning Aortic Dissection Hydrodynamics Models, Cardiovascular
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Refined matrix completion for spectrum estimation of heart rate variability.

Mathematical biosciences and engineering : MBE Aug 2, 2024
Heart rate variability (HRV) is an important metric in cardiovascular health monitoring. Spectral analysis of HRV provides essential insights into the functioning of the cardiac autonomic nervous system. However, data artefacts could degrade signal q...
Electrocardiography Models, Statistical Signal Processing, Computer-Assisted Algorithms Reproducibility of Results Deep Learning Autonomic Nervous System Heart Rate Models, Cardiovascular Uncertainty Humans Machine Learning
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Proteomics-Enabled Deep Learning Machine Algorithms Can Enhance Prediction of Mortality.

Journal of the American College of Cardiology Oct 19, 2021
BACKGROUND: Individualized risk prediction represents a prerequisite for providing personalized medicine.
Follow-Up Studies Models, Cardiovascular Deep Learning Cohort Studies Proteomics Algorithms Female Humans Middle Aged Aged Neural Networks, Computer Risk Assessment Male Cardiovascular Diseases
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'Rise of the machines': the next frontier in individualized medicine.

Cardiovascular research Aug 29, 2021
Humans Machine Learning Diagnosis, Computer-Assisted Wearable Electronic Devices Forecasting Precision Medicine Models, Cardiovascular Telemedicine Diffusion of Innovation Therapy, Computer-Assisted
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Meeting the unmet needs of clinicians from AI systems showcased for cardiology with deep-learning-based ECG analysis.

Proceedings of the National Academy of Sciences of the United States of America Jun 15, 2021
Despite their great promise, artificial intelligence (AI) systems have yet to become ubiquitous in the daily practice of medicine largely due to several crucial unmet needs of healthcare practitioners. These include lack of explanations in clinically...
Time Factors Physicians Humans Cardiology ROC Curve Artificial Intelligence Electrocardiography Uncertainty Reproducibility of Results Algorithms Deep Learning Statistics as Topic Models, Cardiovascular
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Development of a field artificial intelligence triage tool: Confidence in the prediction of shock, transfusion, and definitive surgical therapy in patients with truncal gunshot wounds.

The journal of trauma and acute care surgery Jun 1, 2021
BACKGROUND: In-field triage tools for trauma patients are limited by availability of information, linear risk classification, and a lack of confidence reporting. We therefore set out to develop and test a machine learning algorithm that can overcome ...
Wounds, Gunshot Injury Severity Score Models, Cardiovascular Trauma Centers Feasibility Studies Hemorrhage Retrospective Studies Shock Female Young Adult ROC Curve Humans Adult Blood Transfusion Artificial Intelligence Emergency Medical Services Male Thoracic Injuries Triage Risk Assessment
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