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Models, Cardiovascular

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Artificial intelligence modeling of vascular calcification.

Acta biochimica et biophysica Sinica Dec 11, 2020
Humans Artificial Intelligence Vascular Calcification Models, Cardiovascular
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Inverse mechano-electrical reconstruction of cardiac excitation wave patterns from mechanical deformation using deep learning.

Chaos (Woodbury, N.Y.) Dec 1, 2020
The inverse mechano-electrical problem in cardiac electrophysiology is the attempt to reconstruct electrical excitation or action potential wave patterns from the heart's mechanical deformation that occurs in response to electrical excitation. Becaus...
Computer Simulation Deep Learning Action Potentials Myocytes, Cardiac Electricity Models, Cardiovascular
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Patient-specific three-dimensional aortic arch modeling for automatic measurements: clinical validation in aortic coarctation.

Journal of cardiovascular medicine (Hagerstown, Md.) Jul 1, 2020
AIM: A validated algorithm for automatic aortic arch measurements in aortic coarctation (CoA) patients could standardize procedures for clinical planning.
Humans Machine Learning Software Adolescent Models, Cardiovascular Young Adult Patient-Specific Modeling Child Adult Retrospective Studies Aortic Coarctation Imaging, Three-Dimensional Male Female Reproducibility of Results Aorta, Thoracic Predictive Value of Tests Magnetic Resonance Angiography Automation
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Detection of Hypertrophic Cardiomyopathy Using a Convolutional Neural Network-Enabled Electrocardiogram.

Journal of the American College of Cardiology Feb 25, 2020
BACKGROUND: Hypertrophic cardiomyopathy (HCM) is an uncommon but important cause of sudden cardiac death.
Aged Adult Male Neural Networks, Computer Algorithms Female Models, Cardiovascular Middle Aged Electrocardiography Cardiomyopathy, Hypertrophic Humans
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Machine learning versus traditional risk stratification methods in acute coronary syndrome: a pooled randomized clinical trial analysis.

Journal of thrombosis and thrombolysis Jan 1, 2020
Traditional statistical models allow population based inferences and comparisons. Machine learning (ML) explores datasets to develop algorithms that do not assume linear relationships between variables and outcomes and that may account for higher ord...
Risk Assessment Randomized Controlled Trials as Topic Fibrinolytic Agents Models, Cardiovascular Hemorrhage Acute Coronary Syndrome Aged Male Middle Aged Humans Machine Learning Female
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[Research on the cardiovascular function evaluation system based on noninvasive detection indices].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Aug 25, 2019
Based on the noninvasive detection indeices and fuzzy mathematics method, this paper studied the noninvasive, convenient and economical cardiovascular health assessment system. The health evaluation index of cardiovascular function was built based on...
Humans Research Cardiovascular System Cardiovascular Diseases Models, Cardiovascular Fuzzy Logic
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PPGnet: Deep Network for Device Independent Heart Rate Estimation from Photoplethysmogram.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Photoplethysmogram (PPG) is increasingly used to provide monitoring of the cardiovascular system under ambulatory conditions. Wearable devices like smartwatches use PPG to allow long-term unobtrusive monitoring of heart rate in free-living conditions...
Computer Simulation Deep Learning Humans Algorithms Models, Cardiovascular Wearable Electronic Devices Heart Rate Photoplethysmography Artifacts Signal Processing, Computer-Assisted Monitoring, Ambulatory
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A new deep learning model for assisted diagnosis on electrocardiogram.

Mathematical biosciences and engineering : MBE Mar 22, 2019
In order to enhance the accuracy of computer aided electrocardiogram analysis, we propose a deep learning model called CBRNN to assist diagnosis on electrocardiogram for clinical medical service. It combines two sub networks which are convolutional n...
Humans Models, Cardiovascular Signal Processing, Computer-Assisted Neural Networks, Computer Diagnosis, Computer-Assisted Cardiology Machine Learning Deep Learning Medical Errors Skin Algorithms Electrocardiography Medical Informatics
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Computational Platform Based on Deep Learning for Segmenting Ventricular Endocardium in Long-axis Cardiac MR Imaging.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
This paper presents an automated computational platform based on deep learning (DL) approach for left ventricular (LV) and right ventricular (RV) endocardium segmentation in long-axis cine cardiovascular magnetic resonance (CMR). The proposed method ...
Image Interpretation, Computer-Assisted Endocardium Humans Models, Cardiovascular Reproducibility of Results Neural Networks, Computer Magnetic Resonance Imaging, Cine Algorithms Deep Learning Heart Ventricles
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Teaching cardiovascular medicine to machines.

Cardiovascular research Jul 1, 2018
Diagnosis, Computer-Assisted Humans Diffusion of Innovation Prognosis Therapy, Computer-Assisted Machine Learning Ventricular Remodeling Cardiovascular Diseases Models, Cardiovascular Hemodynamics Patient-Specific Modeling
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