AIMC Topic: Mitral Valve

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Deep learning-based post hoc denoising for 3D volume-rendered cardiac CT in mitral valve prolapse.

The international journal of cardiovascular imaging Apr 23, 2025
We hypothesized that deep learning-based post hoc denoising could improve the quality of cardiac CT for the 3D volume-rendered (VR) imaging of mitral valve (MV) prolapse. We aimed to evaluate the quality of denoised 3D VR images for visualizing MV pr...
Tomography, X-Ray Computed Female Reproducibility of Results Aged Humans Retrospective Studies Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Mitral Valve Mitral Valve Prolapse Male Middle Aged Deep Learning Imaging, Three-Dimensional
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Deep Learning-Enabled Assessment of Right Ventricular Function Improves Prognostication After Transcatheter Edge-to-Edge Repair for Mitral Regurgitation.

Circulation. Cardiovascular imaging Jan 21, 2025
BACKGROUND: Right ventricular (RV) function has a well-established prognostic role in patients with severe mitral regurgitation (MR) undergoing transcatheter edge-to-edge repair (TEER) and is typically assessed using echocardiography-measured tricusp...
Ventricular Function, Right Echocardiography Severity of Illness Index Deep Learning Aged Registries Humans Predictive Value of Tests Aged, 80 and over Mitral Valve Prognosis Male Female Mitral Valve Insufficiency Stroke Volume Cardiac Catheterization
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Robotic navigation with deep reinforcement learning in transthoracic echocardiography.

International journal of computer assisted radiology and surgery Sep 20, 2024
PURPOSE: The search for heart components in robotic transthoracic echocardiography is a time-consuming process. This paper proposes an optimized robotic navigation system for heart components using deep reinforcement learning to achieve an efficient ...
Humans Algorithms Echocardiography Deep Learning Robotic Surgical Procedures Surgery, Computer-Assisted Mitral Valve Reinforcement Machine Learning
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Artificial Intelligence and Mitral Regurgitation: Friend or Foe?

Circulation Sep 16, 2024
Humans Artificial Intelligence Mitral Valve Mitral Valve Insufficiency
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An Automated Machine Learning-Based Quantitative Multiparametric Approach for Mitral Regurgitation Severity Grading.

JACC. Cardiovascular imaging Aug 14, 2024
BACKGROUND: Considering the high prevalence of mitral regurgitation (MR) and the highly subjective, variable MR severity reporting, an automated tool that could screen patients for clinically significant MR (≥ moderate) would streamline the diagnosti...
Mitral Valve Mitral Valve Insufficiency Image Interpretation, Computer-Assisted Automation Severity of Illness Index Predictive Value of Tests Workflow Feasibility Studies Aged Male Middle Aged Machine Learning Prognosis Female Reproducibility of Results Humans
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High-Throughput Deep Learning Detection of Mitral Regurgitation.

Circulation Aug 12, 2024
BACKGROUND: Diagnosis of mitral regurgitation (MR) requires careful evaluation by echocardiography with Doppler imaging. This study presents the development and validation of a fully automated deep learning pipeline for identifying apical 4-chamber v...
Humans Female Aged Male Deep Learning Echocardiography Mitral Valve Middle Aged Mitral Valve Insufficiency Severity of Illness Index Echocardiography, Doppler, Color
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Application of machine learning to predict in-hospital mortality after transcatheter mitral valve repair.

Surgery Aug 9, 2024
INTRODUCTION: Transcatheter mitral valve repair offers a minimally invasive treatment option for patients at high risk for traditional open repair. We sought to develop dynamic machine-learning risk prediction models for in-hospital mortality after t...
Mitral Valve Insufficiency Heart Valve Prosthesis Implantation Cardiac Catheterization Machine Learning Aged, 80 and over Retrospective Studies Male Female Middle Aged Humans Aged Risk Assessment Hospital Mortality United States Mitral Valve
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EasyPISA: Automatic Integrated PISA Measurements of Mitral Regurgitation From 2-D Color-Doppler Using Deep Learning.

Ultrasound in medicine & biology Aug 8, 2024
OBJECTIVE: The proximal isovelocity surface area (PISA) method is a well-established approach for mitral regurgitation (MR) quantification. However, it exhibits high inter-observer variability and inaccuracies in cases of non-hemispherical flow conve...
Mitral Valve Insufficiency Echocardiography, Doppler, Color Humans Retrospective Studies Female Aged Male Middle Aged Deep Learning Mitral Valve
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Deep Learning for Echo Analysis, Tracking, and Evaluation of Mitral Regurgitation (DELINEATE-MR).

Circulation Jun 17, 2024
BACKGROUND: Artificial intelligence, particularly deep learning (DL), has immense potential to improve the interpretation of transthoracic echocardiography (TTE). Mitral regurgitation (MR) is the most common valvular heart disease and presents unique...
Echocardiography Middle Aged Severity of Illness Index Deep Learning Female Aged Male ROC Curve Humans Mitral Valve Mitral Valve Insufficiency
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A complexity evaluation system for mitral valve repair based on preoperative echocardiographic and machine learning.

Hellenic journal of cardiology : HJC = Hellenike kardiologike epitheorese Apr 16, 2024
BACKGROUND: To develop a novel complexity evaluation system for mitral valve repair based on preoperative echocardiographic data and multiple machine learning algorithms.
Stroke Volume Echocardiography Middle Aged Female Mitral Valve Humans Risk Factors Mitral Valve Insufficiency Aged Preoperative Care Machine Learning Male Retrospective Studies
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