AIMC Topic: Coronary Artery Disease
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A lightweight graph neural network to predict long-term mortality in coronary artery disease patients: an interpretable causality-aware approach.
Journal of biomedical informatics
Jul 1, 2025
BACKGROUND: Coronary artery disease (CAD) causes substantial death toll in the United States and worldwide. While traditional methods for CAD mortality prediction are based on established risk factors, they have significant limitations in accuracy, a...
Systemic coagulation-inflammation index in the prediction of ISR in patients undergoing drug-eluting stents implant: A retrospective study based on multiple machine learning methods.
International journal of cardiology
Jul 1, 2025
BACKGROUND: The Systemic Coagulation-Inflammation index (SCI) is an innovative hematological metric that accurately reflects both coagulopathic and inflammatory dynamics. In this paper, the objective of this paper is to explain the prognostic impact ...
Derivation and validation of an artificial intelligence-based plaque burden safety cut-off for long-term acute coronary syndrome from coronary computed tomography angiography.
European heart journal. Cardiovascular Imaging
Jun 30, 2025
AIMS: Artificial intelligence (AI) has enabled accurate and fast plaque quantification from coronary computed tomography angiography (CCTA). However, AI detects any coronary plaque in up to 97% of patients. To avoid overdiagnosis, a plaque burden saf...
Humans
Artificial Intelligence
Female
Reproducibility of Results
Middle Aged
Coronary Angiography
Risk Assessment
Registries
Aged
Follow-Up Studies
Coronary Artery Disease
Sensitivity and Specificity
Predictive Value of Tests
Computed Tomography Angiography
Male
Acute Coronary Syndrome
Plaque, Atherosclerotic
Hybrid strategy of coronary atherosclerosis characterization with T1-weighted MRI and CT angiography to non-invasively predict periprocedural myocardial injury.
European heart journal. Cardiovascular Imaging
Jun 30, 2025
AIMS: Coronary computed tomography angiography (CCTA) and magnetic resonance imaging (MRI) can predict periprocedural myocardial injury (PMI) after percutaneous coronary intervention (PCI). We aimed to investigate whether integrating MRI with CCTA, u...
Cost-effectiveness of a novel AI technology to quantify coronary inflammation and cardiovascular risk in patients undergoing routine coronary computed tomography angiography.
European heart journal. Quality of care & clinical outcomes
Jun 23, 2025
AIMS: Coronary computed tomography angiography (CCTA) is a first-line investigation for chest pain in patients with suspected obstructive coronary artery disease (CAD). However, many acute cardiac events occur in the absence of obstructive CAD. We as...
The Machine Learning Models in Major Cardiovascular Adverse Events Prediction Based on Coronary Computed Tomography Angiography: Systematic Review.
Journal of medical Internet research
Jun 13, 2025
BACKGROUND: Coronary computed tomography angiography (CCTA) has emerged as the first-line noninvasive imaging test for patients at high risk of coronary artery disease (CAD). When combined with machine learning (ML), it provides more valid evidence i...
A Review on the Estimation of Coronary Fractional Flow Reserve Using Artificial Intelligence.
Turk Kardiyoloji Dernegi arsivi : Turk Kardiyoloji Derneginin yayin organidir
Jun 1, 2025
Coronary artery disease (CAD) is the leading cause of death worldwide. The most widely used and precise method for diagnosing CAD is invasive coronary angiography (ICA). Fractional flow reserve (FFR) is an index of the functional severity of coronary...
Identification and validation of inflammatory response genes linking chronic kidney disease with coronary artery disease based on bioinformatics and machine learning.
Scientific reports
Jun 1, 2025
Coronary artery disease (CAD) commonly occurs and elevates the risk of cardiovascular events and mortality in chronic kidney disease (CKD) patients. The underlying pathogenesis of CKD-related CAD is believed to be closely linked to inflammatory respo...
A multi-model deep learning approach for the identification of coronary artery calcifications within 2D coronary angiography images.
International journal of computer assisted radiology and surgery
Jun 1, 2025
PURPOSE: Identifying and quantifying coronary artery calcification (CAC) is crucial for preoperative planning, as it helps to estimate both the complexity of the 2D coronary angiography (2DCA) procedure and the risk of developing intraoperative compl...
Cardiac imaging for the detection of ischemia: current status and future perspectives.
Expert review of medical devices
Jun 1, 2025
INTRODUCTION: Coronary artery disease is the main cause of mortality worldwide mandating early detection, appropriate treatment, and follow-up. Noninvasive cardiac imaging techniques allow detection of obstructive coronary heart disease by direct vis...
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