AIMC Topic: Aortic Valve Stenosis

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Identifying Aortic Stenosis With a Single Parasternal Long-Axis Video Using Deep Learning.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography Oct 30, 2022
Humans Deep Learning Aortic Valve Stenosis Aortic Valve
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Unsupervised clustering of patients with severe aortic stenosis: A myocardial continuum.

Archives of cardiovascular diseases Sep 29, 2022
BACKGROUND: Traditional statistics, based on prediction models with a limited number of prespecified variables, are probably not adequate to provide an appropriate classification of a condition that is as heterogeneous as aortic stenosis (AS).
Ventricular Remodeling Severity of Illness Index Cluster Analysis Aortic Valve Stenosis Aortic Valve Humans Artificial Intelligence Female Aged Male
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A soft robotic sleeve mimicking the haemodynamics and biomechanics of left ventricular pressure overload and aortic stenosis.

Nature biomedical engineering Sep 26, 2022
Preclinical models of aortic stenosis can induce left ventricular pressure overload and coarsely control the severity of aortic constriction. However, they do not recapitulate the haemodynamics and flow patterns associated with the disease. Here we r...
Biomechanical Phenomena Animals Swine Hemodynamics Aortic Valve Stenosis Robotics Ventricular Pressure
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Development of a deep learning-based algorithm for the automatic detection and quantification of aortic valve calcium.

European journal of radiology Feb 6, 2021
PURPOSE: We aimed to develop a deep learning (DL)-based algorithm for automated quantification of aortic valve calcium (AVC) from non-enhanced electrocardiogram-gated cardiac CT scans and compare performance of DL-measured AVC volume and Agatston sco...
Aortic Valve Stenosis Retrospective Studies Aortic Valve Severity of Illness Index Calcium Humans Deep Learning Algorithms Calcinosis
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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 Aged Humans Machine Learning Logistic Models Aortic Valve Stenosis Arrhythmias, Cardiac Transcatheter Aortic Valve Replacement Aged, 80 and over Male Risk Assessment Postoperative Complications Prosthesis Implantation Pacemaker, Artificial
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Network-based screen in iPSC-derived cells reveals therapeutic candidate for heart valve disease.

Science (New York, N.Y.) Dec 10, 2020
Mapping the gene-regulatory networks dysregulated in human disease would allow the design of network-correcting therapies that treat the core disease mechanism. However, small molecules are traditionally screened for their effects on one to several o...
Haploinsufficiency Aortic Valve Disease Aortic Valve Drug Evaluation, Preclinical Thiazoles Gene Expression Regulation Nitriles Small Molecule Libraries Humans Induced Pluripotent Stem Cells Machine Learning Receptor, Notch1 Disease Models, Animal Algorithms Mice, Inbred C57BL Animals Calcinosis RNA-Seq Drug Discovery Aortic Valve Stenosis Gene Regulatory Networks Mice
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Performance of Prediction Models for Diagnosing Severe Aortic Stenosis Based on Aortic Valve Calcium on Cardiac Computed Tomography: Incorporation of Radiomics and Machine Learning.

Korean journal of radiology Nov 3, 2020
OBJECTIVE: We aimed to develop a prediction model for diagnosing severe aortic stenosis (AS) using computed tomography (CT) radiomics features of aortic valve calcium (AVC) and machine learning (ML) algorithms.
Humans Aortic Valve Stenosis Male Machine Learning Aortic Valve Retrospective Studies Calcium Tomography, X-Ray Computed Echocardiography Female Middle Aged Aged Severity of Illness Index
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Classification of aortic stenosis using conventional machine learning and deep learning methods based on multi-dimensional cardio-mechanical signals.

Scientific reports Oct 16, 2020
This paper introduces a study on the classification of aortic stenosis (AS) based on cardio-mechanical signals collected using non-invasive wearable inertial sensors. Measurements were taken from 21 AS patients and 13 non-AS subjects. A feature analy...
Signal Processing, Computer-Assisted Heart Elasticity Wavelet Analysis Finite Element Analysis Biomedical Engineering Deep Learning Pilot Projects Aortic Valve Stenosis Decision Trees Aged Male Middle Aged Machine Learning Algorithms Humans Female Neural Networks, Computer Reproducibility of Results
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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...
Risk Assessment Severity of Illness Index Aortic Valve Stenosis Cohort Studies Female Humans Transcatheter Aortic Valve Replacement Treatment Outcome Aged Machine Learning Aged, 80 and over Phenotype Male
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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).
ROC Curve Aortic Valve Stenosis Aortic Valve Humans Transcatheter Aortic Valve Replacement Prognosis Education, Medical, Graduate Machine Learning Female Algorithms Aged Male
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