AIMC Topic: Coronary Stenosis

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End-to-end deep-learning model for the detection of coronary artery stenosis on coronary CT images.

Open heart Jan 11, 2025
PURPOSE: We examined whether end-to-end deep-learning models could detect moderate (≥50%) or severe (≥70%) stenosis in the left anterior descending artery (LAD), right coronary artery (RCA) or left circumflex artery (LCX) in iodine contrast-enhanced ...
Humans Retrospective Studies Female Severity of Illness Index Deep Learning Predictive Value of Tests Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Reproducibility of Results Aged Male Middle Aged Coronary Vessels Computed Tomography Angiography Coronary Stenosis
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Automated classification of coronary LEsions fRom coronary computed Tomography angiography scans with an updated deep learning model: ALERT study.

European radiology Jan 10, 2025
OBJECTIVES: The use of deep learning models for quantitative measurements on coronary computed tomography angiography (CCTA) may reduce inter-reader variability and increase efficiency in clinical reporting. This study aimed to investigate the diagno...
Male Middle Aged Deep Learning Coronary Angiography Retrospective Studies Female Observer Variation Reproducibility of Results Computed Tomography Angiography Aged Coronary Stenosis Radiographic Image Interpretation, Computer-Assisted Humans Coronary Artery Disease
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Automated stenosis estimation of coronary angiographies using end-to-end learning.

The international journal of cardiovascular imaging Jan 9, 2025
The initial evaluation of stenosis during coronary angiography is typically performed by visual assessment. Visual assessment has limited accuracy compared to fractional flow reserve and quantitative coronary angiography, which are more time-consumin...
Aged Male Middle Aged Severity of Illness Index Humans Retrospective Studies Female Reproducibility of Results Coronary Artery Disease Automation Coronary Vessels Coronary Stenosis Fractional Flow Reserve, Myocardial Deep Learning Predictive Value of Tests Coronary Angiography Radiographic Image Interpretation, Computer-Assisted
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Computerized classification method for significant coronary artery stenosis on whole-heart coronary MRA using 3D convolutional neural networks with attention mechanisms.

Radiological physics and technology Dec 31, 2024
This study aims to develop a computerized classification method for significant coronary artery stenosis on whole-heart coronary magnetic resonance angiography (WHCMRA) images using a 3D convolutional neural network (3D-CNN) with attention mechanisms...
Humans Aged Male Middle Aged Neural Networks, Computer Magnetic Resonance Angiography Female Coronary Stenosis Convolutional Neural Networks Imaging, Three-Dimensional Coronary Angiography Heart
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Noninvasive machine-learning models for the detection of lesion-specific ischemia in patients with stable angina with intermediate stenosis severity on coronary CT angiography.

Physical and engineering sciences in medicine Dec 30, 2024
This study proposed noninvasive machine-learning models for the detection of lesion-specific ischemia (LSI) in patients with stable angina with intermediate stenosis severity based on coronary computed tomography (CT) angiography. This single-center ...
Computed Tomography Angiography Coronary Stenosis Fractional Flow Reserve, Myocardial Humans Machine Learning Severity of Illness Index Retrospective Studies Coronary Angiography Myocardial Ischemia Angina, Stable Female Aged Male Middle Aged
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Artificial Intelligence-Driven Assessment of Coronary Computed Tomography Angiography for Intermediate Stenosis: Comparison With Quantitative Coronary Angiography and Fractional Flow Reserve.

The American journal of cardiology Dec 11, 2024
We aimed to compare artificial intelligence (AI)-based coronary stenosis evaluation of coronary computed tomography angiography (CCTA) with its quantitative counterpart of invasive coronary angiography (ICA) and invasive fractional flow reserve (FFR)...
Computed Tomography Angiography Coronary Stenosis Fractional Flow Reserve, Myocardial Humans Retrospective Studies Artificial Intelligence Female Aged Middle Aged Male Severity of Illness Index Predictive Value of Tests Coronary Angiography Coronary Vessels
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Screening for severe coronary stenosis in patients with apparently normal electrocardiograms based on deep learning.

BMC medical informatics and decision making Nov 22, 2024
BACKGROUND: Patients with severe coronary arterystenosis may present with apparently normal electrocardiograms (ECGs), making it difficult to detect adverse health conditions during routine screenings or physical examinations. Consequently, these pat...
Humans Electrocardiography Male Female Coronary Stenosis Middle Aged Aged Severity of Illness Index Sensitivity and Specificity Deep Learning
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Artificial intelligence-enhanced detection of subclinical coronary artery disease in athletes: diagnostic performance and limitations.

The international journal of cardiovascular imaging Oct 7, 2024
PURPOSE: This study evaluates the diagnostic performance of artificial intelligence (AI)-based coronary computed tomography angiography (CCTA) for detecting coronary artery disease (CAD) and assessing fractional flow reserve (FFR) in asymptomatic mal...
Fractional Flow Reserve, Myocardial Coronary Vessels Asymptomatic Diseases Computed Tomography Angiography Coronary Stenosis Male Middle Aged Severity of Illness Index Predictive Value of Tests Coronary Artery Disease Running Athletes Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Artificial Intelligence Prospective Studies Reproducibility of Results Aged Humans
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Exploration of fractional flow reservation score based on artificial intelligence post-processing for coronary artery lesions in patients with diabetes and coronary heart disease.

SLAS technology Sep 21, 2024
In order to evaluate the relationship between coronary heart disease (CHD) and fractional flow reservation (FFR) in patients with different levels of CHD and diabetes, this paper used AI (artificial intelligence) post-processing technology to detect ...
Coronary Angiography Fractional Flow Reserve, Myocardial Coronary Artery Disease Male Humans Computed Tomography Angiography Coronary Vessels Middle Aged Artificial Intelligence Coronary Stenosis Coronary Disease Image Processing, Computer-Assisted Female Diabetes Mellitus Aged
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Accuracy of deep learning in the differential diagnosis of coronary artery stenosis: a systematic review and meta-analysis.

BMC medical imaging Sep 16, 2024
BACKGROUND: In recent years, as deep learning has received widespread attention in the field of heart disease, some studies have explored the potential of deep learning based on coronary angiography (CAG) or coronary CT angiography (CCTA) images in d...
Diagnosis, Differential Coronary Angiography Computed Tomography Angiography Coronary Stenosis Humans Deep Learning
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