AI Medical Compendium Journal:
Cardiovascular engineering and technology

Showing 1 to 10 of 20 articles

Investigation of Inter-Patient, Intra-Patient, and Patient-Specific Based Training in Deep Learning for Classification of Heartbeat Arrhythmia.

Cardiovascular engineering and technology Feb 26, 2025
Effective diagnosis of electrocardiogram (ECG) is one of the simplest and fastest ways to assess the heart's function. In the recent decade, various attempts have been made to automate the classification of electrocardiogram signals to detect heartbe...
Heart Rate Deep Learning Electrocardiography Action Potentials Predictive Value of Tests Signal Processing, Computer-Assisted Arrhythmias, Cardiac Databases, Factual Reproducibility of Results Diagnosis, Computer-Assisted Humans
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Automated Coronary Artery Segmentation with 3D PSPNET using Global Processing and Patch Based Methods on CCTA Images.

Cardiovascular engineering and technology Feb 20, 2025
The prevalence of coronary artery disease (CAD) has become the major cause of death across the world in recent years. The accurate segmentation of coronary artery is important in clinical diagnosis and treatment of coronary artery disease (CAD) such ...
Reproducibility of Results Deep Learning Imaging, Three-Dimensional Humans Neural Networks, Computer Coronary Artery Disease Coronary Vessels Plaque, Atherosclerotic Computed Tomography Angiography Predictive Value of Tests Coronary Angiography Radiographic Image Interpretation, Computer-Assisted
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Activation of a Soft Robotic Left Ventricular Phantom Embedded in a Closed-Loop Cardiovascular Simulator: A Computational and Experimental Analysis.

Cardiovascular engineering and technology Oct 14, 2024
PURPOSE: Cardiovascular simulators are used in the preclinical testing phase of medical devices. Their reliability increases the more they resemble clinically relevant scenarios. In this study, a physiologically actuated soft robotic left ventricle (...
Humans Robotics Equipment Design Heart Ventricles Phantoms, Imaging Computer Simulation Reproducibility of Results Ventricular Function, Left Finite Element Analysis Models, Cardiovascular
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Review of Machine Learning Techniques in Soft Tissue Biomechanics and Biomaterials.

Cardiovascular engineering and technology Jul 2, 2024
BACKGROUND AND OBJECTIVE: Advanced material models and material characterization of soft biological tissues play an essential role in pre-surgical planning for vascular surgeries and transcatheter interventions. Recent advances in heart valve enginee...
Finite Element Analysis Models, Cardiovascular Materials Testing Biocompatible Materials Tissue Engineering Humans Machine Learning Biomechanical Phenomena Animals Prosthesis Design
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Impact Exploration of Spatiotemporal Feature Derivation and Selection on Machine Learning-Based Predictive Models for Post-Embolization Cerebral Aneurysm Recanalization.

Cardiovascular engineering and technology May 23, 2024
PURPOSE: To enhance the performance of machine learning (ML) models for the post-embolization recanalization of cerebral aneurysms, we evaluated the impact of hemodynamic feature derivation and selection method on six ML algorithms.
Intracranial Aneurysm Spatio-Temporal Analysis Hemodynamics Machine Learning Embolization, Therapeutic Aged Female Male Middle Aged
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Classification Method of ECG Signals Based on RANet.

Cardiovascular engineering and technology Apr 23, 2024
BACKGROUND: Electrocardiograms (ECG) are an important source of information on human heart health and are widely used to detect different types of arrhythmias.
Humans Action Potentials Diagnosis, Computer-Assisted Neural Networks, Computer Deep Learning Arrhythmias, Cardiac Predictive Value of Tests Databases, Factual Electrocardiography Signal Processing, Computer-Assisted Heart Rate Reproducibility of Results
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12-Lead ECG Reconstruction Based on Data From the First Limb Lead.

Cardiovascular engineering and technology Feb 29, 2024
PURPOSE: Electrocardiogram (ECG) data obtained from 12 leads are the most common and informative source for analyzing the cardiovascular system's (CVS) condition in medical practice. However, the large number of electrodes, specific placements on the...
Humans Neural Networks, Computer Predictive Value of Tests Reproducibility of Results Signal Processing, Computer-Assisted Time Factors Heart Rate Electrocardiography Action Potentials
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Aorta Segmentation in 3D CT Images by Combining Image Processing and Machine Learning Techniques.

Cardiovascular engineering and technology Feb 22, 2024
PURPOSE: Aorta segmentation is extremely useful in clinical practice, allowing the diagnosis of numerous pathologies, such as dissections, aneurysms and occlusive disease. In such cases, image segmentation is prerequisite for applying diagnostic algo...
Markov Chains Aorta Computed Tomography Angiography Aortic Diseases Aortography Imaging, Three-Dimensional Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Humans Machine Learning Reproducibility of Results
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Comparison of Machine Learning Algorithms Using Manual/Automated Features on 12-Lead Signal Electrocardiogram Classification: A Large Cohort Study on Students Aged Between 6 to 18 Years Old.

Cardiovascular engineering and technology Oct 17, 2023
PROPOSE: An electrocardiogram (ECG) has been extensively used to detect rhythm disturbances. We sought to determine the accuracy of different machine learning in distinguishing abnormal ECGs from normal ones in children who were examined using a rest...
Child Adult Electrocardiography Adolescent Humans Arrhythmias, Cardiac Cohort Studies Machine Learning Algorithms
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A U-Shaped Network Based on Multi-level Feature and Dual-Attention Coordination Mechanism for Coronary Artery Segmentation of CCTA Images.

Cardiovascular engineering and technology Feb 27, 2023
PURPOSE: Computed tomography coronary angiography (CCTA) images provide optimal visualization of coronary arteries to aid in diagnosing coronary heart disease (CHD). With the deep convolutional neural network, this work aims to develop an intelligent...
Heart Neural Networks, Computer Attention Algorithms Coronary Vessels Image Processing, Computer-Assisted
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