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Coronary Stenosis

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Angiography-Based Machine Learning for Predicting Fractional Flow Reserve in Intermediate Coronary Artery Lesions.

Journal of the American Heart Association Feb 19, 2019
Background An angiography-based supervised machine learning ( ML ) algorithm was developed to classify lesions as having fractional flow reserve ≤0.80 versus >0.80. Methods and Results With a 4:1 ratio, 1501 patients with 1501 intermediate lesions we...
ROC Curve Imaging, Three-Dimensional Middle Aged Severity of Illness Index Coronary Stenosis Fractional Flow Reserve, Myocardial Coronary Angiography Coronary Vessels Humans Female Machine Learning Algorithms Male Retrospective Studies
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CT morphological index provides incremental value to machine learning based CT-FFR for predicting hemodynamically significant coronary stenosis.

International journal of cardiology Aug 15, 2018
AIMS: To study the diagnostic performance of the ratio of Duke jeopardy score (DJS) to the minimal lumen diameter (MLD) at coronary computed tomographic angiography (CCTA) and machine learning based CT-FFR for differentiating functionally significant...
Female Male Machine Learning Retrospective Studies Multidetector Computed Tomography Computed Tomography Angiography Predictive Value of Tests Single-Blind Method Humans Coronary Stenosis Fractional Flow Reserve, Myocardial
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Diagnostic Accuracy of a Machine-Learning Approach to Coronary Computed Tomographic Angiography-Based Fractional Flow Reserve: Result From the MACHINE Consortium.

Circulation. Cardiovascular imaging Jun 1, 2018
BACKGROUND: Coronary computed tomographic angiography (CTA) is a reliable modality to detect coronary artery disease. However, CTA generally overestimates stenosis severity compared with invasive angiography, and angiographic stenosis does not necess...
Computed Tomography Angiography Coronary Stenosis Fractional Flow Reserve, Myocardial Coronary Vessels Asia Coronary Artery Disease Female Reproducibility of Results Aged Male Prospective Studies Retrospective Studies Humans Europe Predictive Value of Tests Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Deep Learning United States Middle Aged Severity of Illness Index
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Improving CCTA-based lesions' hemodynamic significance assessment by accounting for partial volume modeling in automatic coronary lumen segmentation.

Medical physics Mar 1, 2017
PURPOSE: The goal of this study was to assess the potential added benefit of accounting for partial volume effects (PVE) in an automatic coronary lumen segmentation algorithm that is used to determine the hemodynamic significance of a coronary artery...
Datasets as Topic Retrospective Studies Coronary Vessels Machine Learning Hemodynamics Pattern Recognition, Automated Models, Cardiovascular Area Under Curve Humans ROC Curve Software Coronary Stenosis Computed Tomography Angiography Coronary Angiography Imaging, Three-Dimensional
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