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Transcatheter Aortic Valve Replacement

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Development and Application of a System Based on Artificial Intelligence for Transcatheter Aortic Prosthesis Selection.

Brazilian journal of cardiovascular surgery
INTRODUCTION: The interest in Expert systems has increased in the medical area. Some of them are employed even for diagnosis. With the variability of transcatheter prostheses, the most appropriate choice can be complex. This scenario reveals an enabl...

Machine learning-based risk prediction of intrahospital clinical outcomes in patients undergoing TAVI.

Clinical research in cardiology : official journal of the German Cardiac Society
BACKGROUND: Currently, patient selection in TAVI is based upon a multidisciplinary heart team assessment of patient comorbidities and surgical risk stratification. In an era of increasing need for precision medicine and quickly expanding TAVI indicat...

Performance of a Machine Learning Algorithm in Predicting Outcomes of Aortic Valve Replacement.

The Annals of thoracic surgery
BACKGROUND: This study evaluated the performance of a machine learning (ML) algorithm in predicting outcomes of surgical aortic valve replacement (SAVR).

Usefulness of Semisupervised Machine-Learning-Based Phenogrouping to Improve Risk Assessment for Patients Undergoing Transcatheter Aortic Valve Implantation.

The American journal of cardiology
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...

Machine learning method for predicting pacemaker implantation following transcatheter aortic valve replacement.

Pacing and clinical electrophysiology : PACE
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...

Deep learning-based prediction of early cerebrovascular events after transcatheter aortic valve replacement.

Scientific reports
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...