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Coronary Artery Disease

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In-hospital mortality and morbidity after robotic coronary artery surgery.

Journal of cardiothoracic and vascular anesthesia
OBJECTIVES: The objective of this study was to assess the impact of robotic approaches on outcomes of coronary bypass surgery.

[Artificial intelligence-based automated assessment of coronary flow reserve from angiography and the impact of different vasodilators].

Zhonghua xin xue guan bing za zhi
To explore the feasibility of a coronary angiography-based method developed with artificial intelligence which was able to automatically and quickly calculate coronary volumetric blood flow and coronary flow reserve (CFR), and explore the difference...

Diagnostic Accuracy of On-Premise Automated Coronary CT Angiography Analysis Based on Coronary Artery Disease Reporting and Data System 2.0.

Radiology
Background Chest pain is a leading cause of outpatient and emergency department visits; advancements in artificial intelligence (AI) could improve coronary CT angiography (CCTA) workflows for these patients. Purpose To evaluate the performance of an ...

[Coronary computed tomography in the clinical arena. Recent evidence and future perspectives].

Giornale italiano di cardiologia (2006)
In the past few years, computed tomography coronary angiography (CTCA) has rapidly become a widely used diagnostic tool in several clinical settings and is recommended by the European guidelines with a high degree of recommendation in patients with s...

Do positive psychosocial factors contribute to the prediction of coronary artery disease? A UK Biobank-based machine learning approach.

European journal of preventive cardiology
AIMS: Most prediction models for coronary artery disease (CAD) compile biomedical and behavioural risk factors using linear multivariate models. This study explores the potential of integrating positive psychosocial factors (PPFs), including happines...

Deep Learning-based Quantitative CT Myocardial Perfusion Imaging and Risk Stratification of Coronary Artery Disease.

Radiology
Background Precise assessment of myocardial ischemia burden and cardiovascular risk stratification based on dynamic CT myocardial perfusion imaging (MPI) is lacking. Purpose To develop and validate a deep learning (DL) model for automated quantificat...

Machine Learning-Based Immuno-Inflammatory Index Integrating Clinical Characteristics for Predicting Coronary Artery Plaque Rupture.

Immunity, inflammation and disease
BACKGROUND: Coronary artery plaque rupture (PR) is closely associated with immune-inflammatory responses. The systemic inflammatory index (SII) and the systemic inflammatory response index (SIRI) have shown potential in predicting the occurrence of P...

Expanding interpretability through complexity reduction in machine learning-based modelling of cardiovascular disease: A myocardial perfusion imaging PET/CT prognostic study.

European journal of clinical investigation
BACKGROUND: Machine learning-based analysis can be used in myocardial perfusion imaging data to improve risk stratification and the prediction of major adverse cardiovascular events for patients with suspected or established coronary artery disease. ...