AIMC Topic: Coronary Artery Disease
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Diagnostic Accuracy of On-Premise Automated Coronary CT Angiography Analysis Based on Coronary Artery Disease Reporting and Data System 2.0.
Radiology
May 1, 2025
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)
May 1, 2025
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...
Fully Automated Agatston Score Calculation From Electrocardiography-Gated Cardiac Computed Tomography Using Deep Learning and Multi-Organ Segmentation: A Validation Study.
Angiology
May 1, 2025
To evaluate deep learning-based calcium segmentation and quantification on ECG-gated cardiac CT scans compared with manual evaluation. Automated calcium quantification was performed using a neural network based on mask regions with convolutional neur...
Radiographic Image Interpretation, Computer-Assisted
Coronary Artery Disease
Vascular Calcification
Computed Tomography Angiography
Cardiac-Gated Imaging Techniques
Deep Learning
Electrocardiography
Predictive Value of Tests
Coronary Angiography
Female
Humans
Reproducibility of Results
Neural Networks, Computer
Aged
Retrospective Studies
Male
Tomography, X-Ray Computed
Middle Aged
Do positive psychosocial factors contribute to the prediction of coronary artery disease? A UK Biobank-based machine learning approach.
European journal of preventive cardiology
Apr 22, 2025
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
Apr 1, 2025
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
Apr 1, 2025
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
Apr 1, 2025
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. ...
Deep Learning-Based Computer-Aided Diagnosis in Coronary Artery Calcium-Scoring CT for Pulmonary Nodule Detection: A Preliminary Study.
Yonsei medical journal
Apr 1, 2025
PURPOSE: To evaluate the feasibility and utility of deep learning-based computer-aided diagnosis (DL-CAD) for the detection of pulmonary nodules on coronary artery calcium (CAC)-scoring computed tomography (CT).
Comparative Evaluation of Pre-Test Probability Models for Coronary Artery Disease with Assessment of a New Machine Learning-Based Model.
Yonsei medical journal
Apr 1, 2025
PURPOSE: This study aimed to validate pivotal pre-test probability (PTP)-coronary artery disease (CAD) models (CAD consortium model and IJC-CAD model).
Automated proximal coronary artery calcium identification using artificial intelligence: advancing cardiovascular risk assessment.
European heart journal. Cardiovascular Imaging
Mar 3, 2025
AIMS: Identification of proximal coronary artery calcium (CAC) may improve prediction of major adverse cardiac events (MACE) beyond the CAC score, particularly in patients with low CAC burden. We investigated whether the proximal CAC can be detected ...
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