AIMC Topic: Coronary Angiography

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Clinical Performance Evaluation of an Artificial Intelligence-Based Tool for Predicting the Presence of Obstructive Coronary Artery Disease: Protocol for a Cohort Observational Study.

JMIR research protocols
BACKGROUND: A significant number of individuals undergoing coronary computed tomography angiography (CCTA) for suspected (CAD) have nonobstructive or no CAD. There is a need for clinically proven models that can predict the pretest probability of sta...

Hyperparameter optimization of YOLO models for invasive coronary angiography lesion detection and assessment.

Computers in biology and medicine
Coronary artery disease (CAD) remains the leading cause of mortality, creating an urgent need for reproducible, image-based decision support. Although YOLOv8-based detectors underpin much of today's state-of-the-art stenosis detection, their accuracy...

Prediction of Percutaneous Coronary Intervention Success in Patients With Moderate to Severe Coronary Artery Calcification Using Machine Learning Based on Coronary Angiography: Prospective Cohort Study.

Journal of medical Internet research
BACKGROUND: Given the challenges faced during percutaneous coronary intervention (PCI) for heavily calcified lesions, accurately predicting PCI success is crucial for enhancing patient outcomes and optimizing procedural strategies.

Metaverse-based deep learning framework for coronary artery stenosis classification using Monte Carlo Dropout-based ResNet-152.

Computers in biology and medicine
Metaverse offers an immersive healthcare platform that combines virtual reality (VR) and artificial intelligence (AI), providing a new approach to medical diagnostics. However, difficulties such as inadequate spatial resolution, uncertainty managemen...

Knowledge, attitudes, and practices of cardiovascular health care personnel regarding coronary CTA and AI-assisted diagnosis: a cross-sectional study.

Journal of global health
BACKGROUND: Artificial intelligence (AI) holds significant promise for medical applications, particularly in coronary computed tomography angiography (CTA). We assessed the knowledge, attitudes, and practices (KAP) of cardiovascular health care perso...

Interpretable machine learning analysis of immunoinflammatory biomarkers for predicting CHD among NAFLD patients.

Cardiovascular diabetology
BACKGROUND: Coronary Heart Disease (CHD) and Non-Alcoholic Fatty Liver Disease (NAFLD) share overlapping pathogenic mechanisms including adipose tissue dysfunction, insulin resistance, and systemic inflammation mediated by adipokines. However, the sp...

Deep learning-based post-hoc noise reduction improves quarter-radiation-dose coronary CT angiography.

European journal of radiology
PURPOSE: To evaluate the impact of deep learning-based post-hoc noise reduction (DLNR) on image quality, coronary artery disease reporting and data system (CAD-RADS) assessment, and diagnostic performance in quarter-dose versus full-dose coronary CT ...

Dual energy CT-based Radiomics for identification of myocardial focal scar and artificial beam-hardening.

International journal of cardiology
BACKGROUND: Computed tomography is an inadequate method for detecting myocardial focal scar (MFS) due to its moderate density resolution, which is insufficient for distinguishing MFS from artificial beam-hardening (BH). Virtual monochromatic images (...

Two birds with one stone: pre-TAVI coronary CT angiography combined with FFR helps screen for coronary stenosis.

BMC medical imaging
OBJECTIVES: Since coronary artery disease (CAD) is a common comorbidity in patients with aortic valve stenosis, invasive coronary angiography (ICA) can be avoided if significant CAD can be screened with the non-invasive coronary CT angiography (cCTA)...