AIMC Topic: Models, Cardiovascular

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Using intravascular ultrasound image-based fluid-structure interaction models and machine learning methods to predict human coronary plaque vulnerability change.

Computer methods in biomechanics and biomedical engineering Jul 22, 2020
Plaque vulnerability prediction is of great importance in cardiovascular research. In vivo follow-up intravascular ultrasound (IVUS) coronary plaque data were acquired from nine patients to construct fluid-structure interaction models to obtain plaqu...
Coronary Vessels Plaque, Atherosclerotic Models, Cardiovascular Area Under Curve Coronary Angiography Ultrasonography, Interventional Linear Models Female Risk Factors Humans Biomechanical Phenomena Machine Learning Male Middle Aged Ultrasonography ROC Curve Imaging, Three-Dimensional Support Vector Machine
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Classification of heart sounds based on the combination of the modified frequency wavelet transform and convolutional neural network.

Medical & biological engineering & computing Jul 7, 2020
We purpose a novel method that combines modified frequency slice wavelet transform (MFSWT) and convolutional neural network (CNN) for classifying normal and abnormal heart sounds. A hidden Markov model is used to find the position of each cardiac cyc...
Humans Neural Networks, Computer Wavelet Analysis Models, Cardiovascular Algorithms Biomedical Engineering Cardiovascular Diseases Heart Sounds Diagnosis, Computer-Assisted Phonocardiography Signal Processing, Computer-Assisted Markov Chains
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Missing Value Estimation Methods Research for Arrhythmia Classification Using the Modified Kernel Difference-Weighted KNN Algorithms.

BioMed research international Jun 21, 2020
Electrocardiogram (ECG) signal is critical to the classification of cardiac arrhythmia using some machine learning methods. In practice, the ECG datasets are usually with multiple missing values due to faults or distortion. Unfortunately, many establ...
Arrhythmias, Cardiac Humans Electronic Data Processing Machine Learning Models, Cardiovascular Computational Biology Electrocardiography
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Preprocedure Application of Machine Learning and Mechanistic Simulations Predicts Likelihood of Paroxysmal Atrial Fibrillation Recurrence Following Pulmonary Vein Isolation.

Circulation. Arrhythmia and electrophysiology Jun 14, 2020
BACKGROUND: Pulmonary vein isolation (PVI) is an effective treatment strategy for patients with atrial fibrillation (AF), but many experience AF recurrence and require repeat ablation procedures. The goal of this study was to develop and evaluate a m...
Reproducibility of Results Risk Factors Aged Male Middle Aged Humans Machine Learning Retrospective Studies Female Action Potentials Predictive Value of Tests Atrial Fibrillation Heart Rate Catheter Ablation Risk Assessment Diagnosis, Computer-Assisted Treatment Outcome Contrast Media Magnetic Resonance Imaging Patient-Specific Modeling Pulmonary Veins Meglumine Proof of Concept Study Organometallic Compounds Recurrence Models, Cardiovascular
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Machine learning provides evidence that stroke risk is not linear: The non-linear Framingham stroke risk score.

PloS one May 21, 2020
Current stroke risk assessment tools presume the impact of risk factors is linear and cumulative. However, both novel risk factors and their interplay influencing stroke incidence are difficult to reveal using traditional additive models. The goal of...
Nonlinear Dynamics Models, Cardiovascular Boston Algorithms Electrocardiography Aged Humans Prospective Studies Decision Trees Male Female Machine Learning Stroke Risk Factors Middle Aged Hematocrit Risk Assessment Cohort Studies
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Non - invasive modelling methodology for the diagnosis of coronary artery disease using fuzzy cognitive maps.

Computer methods in biomechanics and biomedical engineering May 20, 2020
Cardiovascular diseases (CVD) and strokes produce immense health and economic burdens globally. Coronary Artery Disease (CAD) is the most common type of cardiovascular disease. Coronary Angiography, which is an invasive approach for detection and tre...
Algorithms Female Male ROC Curve Decision Support Systems, Clinical Fuzzy Logic Coronary Artery Disease Databases as Topic Models, Cardiovascular Humans
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Improving an Intelligent Detection System for Coronary Heart Disease Using a Two-Tier Classifier Ensemble.

BioMed research international Apr 27, 2020
Coronary heart disease (CHD) is one of the severe health issues and is one of the most common types of heart diseases. It is the most frequent cause of mortality across the globe due to the lack of a healthy lifestyle. Owing to the fact that a heart ...
Humans Machine Learning Databases, Factual Diagnosis, Computer-Assisted Coronary Disease Models, Cardiovascular
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Development of a prediction model for hypotension after induction of anesthesia using machine learning.

PloS one Apr 16, 2020
Arterial hypotension during the early phase of anesthesia can lead to adverse outcomes such as a prolonged postoperative stay or even death. Predicting hypotension during anesthesia induction is complicated by its diverse causes. We investigated the ...
Neural Networks, Computer Machine Learning Retrospective Studies Electronic Health Records Female Aged Adult Drug Delivery Systems Male Humans Arterial Pressure Anesthesia, General Middle Aged Models, Cardiovascular Bayes Theorem Risk Assessment Anesthetics Feasibility Studies Monitoring, Intraoperative Intubation, Intratracheal Hypotension ROC Curve Cholecystectomy, Laparoscopic
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Applying Deep Neural Networks over Homomorphic Encrypted Medical Data.

Computational and mathematical methods in medicine Apr 9, 2020
In recent years, powered by state-of-the-art achievements in a broad range of areas, machine learning has received considerable attention from the healthcare sector. Despite their ability to provide solutions within personalized medicine, strict regu...
Privacy Computer Security Medical Records Models, Cardiovascular Hemodynamics Deep Learning Humans Coronary Angiography Neural Networks, Computer Feasibility Studies Algorithms Databases, Factual Precision Medicine
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Video-based AI for beat-to-beat assessment of cardiac function.

Nature Mar 25, 2020
Accurate assessment of cardiac function is crucial for the diagnosis of cardiovascular disease, screening for cardiotoxicity and decisions regarding the clinical management of patients with a critical illness. However, human assessment of cardiac fun...
Heart Diseases Video Recording Datasets as Topic Deep Learning Models, Cardiovascular Humans Heart Heart Failure Prospective Studies Atrial Fibrillation Reproducibility of Results Ventricular Function, Left Echocardiography Hospitals
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