AIMC Topic: Transcatheter Aortic Valve Replacement

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The Feasibility of Deep Learning-Based Reconstruction for Low-Tube-Voltage CT Angiography for Transcatheter Aortic Valve Implantation.

Journal of computer assisted tomography Aug 11, 2023
OBJECTIVE: The purpose of this study is to evaluate the efficacy of deep learning reconstruction (DLR) on low-tube-voltage computed tomographic angiography (CTA) for transcatheter aortic valve implantation (TAVI).
Humans Feasibility Studies Radiation Dosage Computed Tomography Angiography Transcatheter Aortic Valve Replacement Algorithms Deep Learning Radiographic Image Interpretation, Computer-Assisted
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A CT-based deep learning system for automatic assessment of aortic root morphology for TAVI planning.

Computers in biology and medicine Jun 7, 2023
Accurate planning of transcatheter aortic valve implantation (TAVI) is important to minimize complications, and it requires anatomic evaluation of the aortic root (AR), commonly performed through 3D computed tomography (CT) image analysis. Currently,...
Aortic Valve Aorta, Thoracic Humans Transcatheter Aortic Valve Replacement Tomography, X-Ray Computed Deep Learning Aortic Valve Stenosis
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Soft robotic patient-specific hydrodynamic model of aortic stenosis and ventricular remodeling.

Science robotics Feb 22, 2023
Aortic stenosis (AS) affects about 1.5 million people in the United States and is associated with a 5-year survival rate of 20% if untreated. In these patients, aortic valve replacement is performed to restore adequate hemodynamics and alleviate symp...
Treatment Outcome Humans Aortic Valve Stenosis Robotics United States Ventricular Remodeling Transcatheter Aortic Valve Replacement Hydrodynamics
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CT Image Feature Diagnosis on the Basis of Deep Learning Algorithm for Preoperative Patients and Complications of Transcatheter Aortic Valve Implantation.

Journal of healthcare engineering Nov 29, 2021
This work was aimed to explore the role of CT angiography information provided by deep learning algorithm in the diagnosis and complications of the disease focusing on congenital aortic valve disease and severe aortic valve stenosis. 120 patients who...
Computed Tomography Angiography Transcatheter Aortic Valve Replacement Deep Learning Treatment Outcome Aortic Valve Humans Algorithms
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Deep learning-based prediction of early cerebrovascular events after transcatheter aortic valve replacement.

Scientific reports Sep 21, 2021
Cerebrovascular events (CVE) are among the most feared complications of transcatheter aortic valve replacement (TAVR). CVE appear difficult to predict due to their multifactorial origin incompletely explained by clinical predictors. We aimed to build...
Female Risk Factors Aged Aged, 80 and over Humans Prospective Studies Tomography, X-Ray Computed Stroke Transcatheter Aortic Valve Replacement Male Deep Learning Incidence
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Predicting Infective Endocarditis After Transcatheter Aortic Valve Implantation Via a Risk Model.

The American journal of cardiology May 9, 2021
Age Factors Predictive Value of Tests Endocarditis Transcatheter Aortic Valve Replacement Male Postoperative Complications United States Female Risk Factors Humans Machine Learning
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Machine Learning Algorithms for Prediction of Permanent Pacemaker Implantation After Transcatheter Aortic Valve Replacement.

Circulation. Arrhythmia and electrophysiology Mar 9, 2021
Transcatheter Aortic Valve Replacement Pacemaker, Artificial Atrioventricular Block Predictive Value of Tests Cardiac Pacing, Artificial Heart Rate Treatment Outcome Action Potentials Aortic Valve Humans Machine Learning Decision Support Techniques Risk Factors Prospective Studies Risk Assessment Retrospective Studies
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Machine learning method for predicting pacemaker implantation following transcatheter aortic valve replacement.

Pacing and clinical electrophysiology : PACE Jan 28, 2021
BACKGROUND: An accurate assessment of permanent pacemaker implantation (PPI) risk following transcatheter aortic valve replacement (TAVR) is important for clinical decision making. The aims of this study were to investigate the significance and utili...
Forecasting Retrospective Studies Female Male Risk Assessment Aged Aged, 80 and over Humans Machine Learning Arrhythmias, Cardiac Postoperative Complications Transcatheter Aortic Valve Replacement Logistic Models Prosthesis Implantation Aortic Valve Stenosis Pacemaker, Artificial
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Usefulness of Semisupervised Machine-Learning-Based Phenogrouping to Improve Risk Assessment for Patients Undergoing Transcatheter Aortic Valve Implantation.

The American journal of cardiology Sep 15, 2020
Semisupervised machine-learning methods are able to learn from fewer labeled patient data. We illustrate the potential use of a semisupervised automated machine-learning (AutoML) pipeline for phenotyping patients who underwent transcatheter aortic va...
Aged Humans Machine Learning Severity of Illness Index Aged, 80 and over Aortic Valve Stenosis Cohort Studies Male Phenotype Transcatheter Aortic Valve Replacement Treatment Outcome Risk Assessment Female
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Performance of a Machine Learning Algorithm in Predicting Outcomes of Aortic Valve Replacement.

The Annals of thoracic surgery Jul 17, 2020
BACKGROUND: This study evaluated the performance of a machine learning (ML) algorithm in predicting outcomes of surgical aortic valve replacement (SAVR).
Male Prognosis Humans Female Machine Learning ROC Curve Transcatheter Aortic Valve Replacement Aortic Valve Algorithms Education, Medical, Graduate Aortic Valve Stenosis Aged
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