AIMC Topic: Coronary Artery Disease

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Accuracy of Machine Learning in Discriminating Kawasaki Disease and Other Febrile Illnesses: Systematic Review and Meta-Analysis.

Journal of medical Internet research Nov 18, 2024
BACKGROUND: Kawasaki disease (KD) is an acute pediatric vasculitis that can lead to coronary artery aneurysms and severe cardiovascular complications, often presenting with obvious fever in the early stages. In current clinical practice, distinguishi...
Mucocutaneous Lymph Node Syndrome Diagnosis, Differential Coronary Artery Disease Fever Humans Machine Learning Child
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Impact of tooth loss and patient characteristics on coronary artery calcium score classification and prediction.

Scientific reports Nov 16, 2024
This study, for the first time, explores the integration of data science and machine learning for the classification and prediction of coronary artery calcium (CAC) scores. It focuses on tooth loss and patient characteristics as key input features to...
Humans Machine Learning Female Risk Factors Coronary Artery Disease Aged Tooth Loss Calcium Adult Coronary Vessels Male Vascular Calcification Middle Aged
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Screening of CAD-related secretory genes associated with type II diabetes based on comprehensive bioinformatics analysis and machine learning.

BMC cardiovascular disorders Nov 5, 2024
BACKGROUND: Type II diabetes mellitus (T2DM) is strongly linked with a heightened risk of coronary artery disease (CAD). Exploring biological targets common to T2DM and CAD is essential for CAD intervention strategies.
Coronary Artery Disease Myocytes, Cardiac Myocytes, Smooth Muscle Fibroblast Growth Factor 7 Genetic Predisposition to Disease Computational Biology Databases, Genetic Aged Male Middle Aged Gene Expression Profiling Transcriptome Humans Diabetes Mellitus, Type 2 Machine Learning Single-Cell Analysis Female Gene Regulatory Networks
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Leveraging machine learning to enhance postoperative risk assessment in coronary artery bypass grafting patients with unprotected left main disease: a retrospective cohort study.

International journal of surgery (London, England) Nov 1, 2024
BACKGROUND: Risk stratification for patients undergoing coronary artery bypass surgery (CABG) for left main coronary artery (LMCA) disease is essential for informed decision-making. This study explored the potential of machine learning (ML) methods t...
Coronary Artery Disease Coronary Artery Bypass Risk Assessment Postoperative Complications Hospital Mortality Humans Machine Learning Retrospective Studies Female Risk Factors Aged Male Middle Aged
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Artificial Intelligence-Based Fully Automated Quantitative Coronary Angiography vs Optical Coherence Tomography-Guided PCI: The FLASH Trial.

JACC. Cardiovascular interventions Oct 30, 2024
BACKGROUND: Recently developed artificial intelligence-based coronary angiography (AI-QCA, fully automated) provides real-time, objective, and reproducible quantitative analysis of coronary angiography without requiring additional time or labor.
Coronary Vessels Middle Aged Stents Image Interpretation, Computer-Assisted Time Factors Treatment Outcome Automation Predictive Value of Tests Tomography, Optical Coherence Humans Republic of Korea Coronary Angiography Artificial Intelligence Female Percutaneous Coronary Intervention Prospective Studies Aged Coronary Artery Disease Male
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Coronary Artery Disease Detection Based on a Novel Multi-Modal Deep-Coding Method Using ECG and PCG Signals.

Sensors (Basel, Switzerland) Oct 29, 2024
Coronary artery disease (CAD) is an irreversible and fatal disease. It necessitates timely and precise diagnosis to slow CAD progression. Electrocardiogram (ECG) and phonocardiogram (PCG), conveying abundant disease-related information, are prevalent...
Humans Neural Networks, Computer Algorithms Support Vector Machine Signal Processing, Computer-Assisted Female Coronary Artery Disease Male Phonocardiography Middle Aged Electrocardiography
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Meta-analysis of deep learning approaches for automated coronary artery calcium scoring: Performance and clinical utility AI in CAC scoring: A meta-analysis: AI in CAC scoring: A meta-analysis.

Computers in biology and medicine Oct 23, 2024
INTRODUCTION: Manual Coronary Artery Calcium (CAC) scoring, crucial for assessing coronary artery disease risk, is time-consuming and variable. Deep learning, particularly through Convolutional Neural Networks (CNNs), promises to automate and enhance...
Humans Artificial Intelligence Vascular Calcification Deep Learning Coronary Artery Disease Calcium Coronary Vessels
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Automated AI-based coronary calcium scoring using retrospective CT data from SCAPIS is accurate and correlates with expert scoring.

European radiology Oct 18, 2024
OBJECTIVES: Evaluation of the correlation and agreement between AI and semi-automatic evaluations of calcium scoring CT (CSCT) examinations using extensive data from the Swedish CardioPulmonary bio-Image study (SCAPIS).
Humans Middle Aged Artificial Intelligence Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Retrospective Studies Female Vascular Calcification Tomography, X-Ray Computed Reproducibility of Results Sweden Male
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Coronary artery calcium measurement on attenuation correction computed tomography using artificial intelligence: correlation with coronary flow capacity and prognosis.

European journal of nuclear medicine and molecular imaging Oct 15, 2024
PURPOSE: This study aimed to test whether the coronary artery calcium (CAC) burden on attenuation correction computed tomography (CTac), measured using artificial intelligence (AI-CACac), correlates with coronary flow capacity (CFC) and prognosis.
Prognosis Retrospective Studies Tomography, X-Ray Computed Female Coronary Artery Disease Aged Calcium Male Coronary Vessels Middle Aged Coronary Circulation Image Processing, Computer-Assisted Humans Artificial Intelligence
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HAGMN-UQ: Hyper association graph matching network with uncertainty quantification for coronary artery semantic labeling.

Medical image analysis Oct 11, 2024
Coronary artery disease (CAD) is one of the leading causes of death worldwide. Accurate extraction of individual arterial branches from invasive coronary angiograms (ICA) is critical for CAD diagnosis and detection of stenosis. Generating semantic se...
Humans Neural Networks, Computer Algorithms Semantics Deep Learning Uncertainty Coronary Angiography Coronary Artery Disease
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