AIMC Topic: Coronary Angiography

Clear Filters Showing 291 to 300 of 435 articles

Identification and Quantification of Cardiovascular Structures From CCTA: An End-to-End, Rapid, Pixel-Wise, Deep-Learning Method.

JACC. Cardiovascular imaging Oct 11, 2019
OBJECTIVES: This study designed and evaluated an end-to-end deep learning solution for cardiac segmentation and quantification.
Humans Prospective Studies Female Reproducibility of Results Aged Radiographic Image Interpretation, Computer-Assisted Registries Heart Diseases Multidetector Computed Tomography Computed Tomography Angiography Male Middle Aged Deep Learning Predictive Value of Tests Coronary Angiography
View on PubMed DOI

Intelligently Advancing Cardiovascular Health Care.

JACC. Cardiovascular interventions Sep 25, 2019
Patient Safety Treatment Outcome Coronary Angiography Arterial Pressure Humans Artificial Intelligence Machine Learning
View on PubMed DOI

Artificial Intelligence for Aortic Pressure Waveform Analysis During Coronary Angiography: Machine Learning for Patient Safety.

JACC. Cardiovascular interventions Sep 25, 2019
OBJECTIVES: This study developed a neural network to perform automated pressure waveform analysis and allow real-time accurate identification of damping.
Neural Networks, Computer Machine Learning Patient Safety Databases, Factual Female Humans Europe Predictive Value of Tests Coronary Angiography Coronary Artery Disease Heart Rate Reproducibility of Results Risk Factors Aged Male Middle Aged Cardiac Catheterization Artifacts Observer Variation Arterial Pressure Aorta
View on PubMed DOI

Detection of Hemodynamically Significant Coronary Stenosis: CT Myocardial Perfusion versus Machine Learning CT Fractional Flow Reserve.

Radiology Sep 24, 2019
Background Direct intraindividual comparison of dynamic CT myocardial perfusion imaging (MPI) and machine learning (ML)-based CT fractional flow reserve (FFR) has not been explored for diagnosing hemodynamically significant coronary artery disease. P...
Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Computed Tomography Angiography Coronary Stenosis Female Fractional Flow Reserve, Myocardial Male Aged Middle Aged Humans Aged, 80 and over Severity of Illness Index Machine Learning Hemodynamics Adult Prospective Studies ROC Curve Sensitivity and Specificity Tomography, X-Ray Computed
View on PubMed DOI

Machine learning based risk prediction model for asymptomatic individuals who underwent coronary artery calcium score: Comparison with traditional risk prediction approaches.

Journal of cardiovascular computed tomography Sep 23, 2019
BACKGROUND: Machine learning (ML) is a computer algorithm used to identify patterns for prediction in various tasks, and ML methods have been beneficial for developing prediction models when applied to heterogeneous and large datasets. We aim to exam...
Health Status Predictive Value of Tests Coronary Angiography Registries Coronary Artery Disease Adult Male Retrospective Studies Vascular Calcification Humans Middle Aged Republic of Korea Asymptomatic Diseases Machine Learning Risk Assessment Female Decision Support Techniques Time Factors Risk Factors Databases, Factual Prognosis
View on PubMed DOI

Cath Lab Robotics: Paradigm Change in Interventional Cardiology?

Current cardiology reports Aug 31, 2019
PURPOSE OF REVIEW: To review the contemporary evidence for robotic-assisted percutaneous coronary and vascular interventions, discussing its current capabilities, limitations, and potential future applications.
Cardiology Coronary Artery Disease Therapy, Computer-Assisted Radiation Injuries Radiation Exposure Humans Treatment Outcome Robotics Coronary Angiography Percutaneous Coronary Intervention
View on PubMed DOI

Diagnostic Performance of Machine Learning Based CT-FFR in Detecting Ischemia in Myocardial Bridging and Concomitant Proximal Atherosclerotic Disease.

The Canadian journal of cardiology Aug 27, 2019
BACKGROUND: The diagnostic performance of coronary computed tomography angiography-derived fractional flow reserve (CT-FFR) in detecting ischemia in myocardial bridging (MB) has not been investigated to date.
Atherosclerosis Humans Male Multidetector Computed Tomography Myocardial Bridging Machine Learning Middle Aged Computed Tomography Angiography Retrospective Studies Severity of Illness Index Coronary Stenosis Female ROC Curve Fractional Flow Reserve, Myocardial Coronary Angiography
View on PubMed DOI

Influence of Coronary Calcium on Diagnostic Performance of Machine Learning CT-FFR: Results From MACHINE Registry.

JACC. Cardiovascular imaging Aug 14, 2019
OBJECTIVES: This study was conducted to investigate the influence of coronary artery calcium (CAC) score on the diagnostic performance of machine-learning-based coronary computed tomography (CT) angiography (cCTA)-derived fractional flow reserve (CT-...
Aged Male Middle Aged Severity of Illness Index Diagnosis, Computer-Assisted Europe Predictive Value of Tests Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Registries Humans Machine Learning Female North America Reproducibility of Results Coronary Artery Disease Vascular Calcification Asia Computed Tomography Angiography Fractional Flow Reserve, Myocardial
View on PubMed DOI

Impact of Coronary Computerized Tomography Angiography-Derived Plaque Quantification and Machine-Learning Computerized Tomography Fractional Flow Reserve on Adverse Cardiac Outcome.

The American journal of cardiology Aug 8, 2019
This study investigated the impact of coronary CT angiography (cCTA)-derived plaque markers and machine-learning-based CT-derived fractional flow reserve (CT-FFR) to identify adverse cardiac outcome. Data of 82 patients (60 ± 11 years, 62% men) who u...
ROC Curve United States Follow-Up Studies Coronary Angiography Humans Coronary Vessels Female Machine Learning Multidetector Computed Tomography Survival Rate Prognosis Plaque, Atherosclerotic Male Retrospective Studies Computed Tomography Angiography Middle Aged Coronary Stenosis Severity of Illness Index Fractional Flow Reserve, Myocardial
View on PubMed DOI

Improved diagnostic accuracy for myocardial perfusion imaging using artificial neural networks on different input variables including clinical and quantification data.

Revista espanola de medicina nuclear e imagen molecular Aug 8, 2019
OBJECTIVE: Diagnostic accuracy of myocardial perfusion imaging (MPI) is not optimal to predict the result of angiography. The current study aimed at investigating the application of artificial neural network (ANN) to integrate the clinical data with ...
Reproducibility of Results Male Coronary Angiography Coronary Artery Disease Humans Myocardial Perfusion Imaging Neural Networks, Computer Retrospective Studies Female
View on PubMed DOI
Popular Topics
Recent Journals