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Coronary Artery Disease

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Enhancing quantitative coronary angiography (QCA) with advanced artificial intelligence: comparison with manual QCA and visual estimation.

The international journal of cardiovascular imaging
Artificial intelligence-based quantitative coronary angiography (AI-QCA) was introduced to address manual QCA's limitations in reproducibility and correction process. The present study aimed to assess the performance of an updated AI-QCA solution (MP...

Identification of biomarkers associated with coronary artery disease and non-alcoholic fatty liver disease by bioinformatics analysis and machine learning.

Scientific reports
The constantly emerging evidence indicates a close association between coronary artery disease (CAD) and non-alcoholic fatty liver disease (NAFLD). However, the exact mechanisms underlying their mutual relationship remain undefined. This study aims t...

Integrative Machine Learning of Glioma and Coronary Artery Disease Reveals Key Tumour Immunological Links.

Journal of cellular and molecular medicine
It is critical to appreciate the role of the tumour-associated microenvironment (TME) in developing strategies for the effective therapy of cancer, as it is an important factor that determines the evolution and treatment response of tumours. This wor...

Machine learning-driven prediction of medical expenses in triple-vessel PCI patients using feature selection.

BMC health services research
Revascularization therapies, such as percutaneous coronary intervention (PCI) and coronary artery bypass grafting (CABG), alleviate symptoms and treat myocardial ischemia. Patients with multivessel disease, particularly those undergoing 3-vessel PCI,...

Identifying semaphorin 3C as a biomarker for sarcopenia and coronary artery disease via bioinformatics and machine learning.

Archives of gerontology and geriatrics
OBJECTIVE: Sarcopenia not only affects patients' quality of life but also may exacerbate the pathological processes of coronary artery disease (CAD). This study aimed to identify potential biomarkers to improve the combined diagnosis and treatment of...

Integrative bioinformatics and machine learning approach unveils potential biomarkers linking coronary atherosclerosis and fatty acid metabolism-associated gene.

Journal of cardiothoracic surgery
BACKGROUND: Atherosclerosis (AS) is increasingly recognized as a chronic inflammatory disease that significantly compromises vascular health and acts as a major contributor to cardiovascular diseases. Advancements in lipidomics and metabolomics have ...

Artificial intelligence applied in identifying left ventricular walls in myocardial perfusion scintigraphy images: Pilot study.

PloS one
This paper proposes the use of artificial intelligence techniques, specifically the nnU-Net convolutional neural network, to improve the identification of left ventricular walls in images of myocardial perfusion scintigraphy, with the objective of im...

A Machine Learning Model Using Cardiac CT and MRI Data Predicts Cardiovascular Events in Obstructive Coronary Artery Disease.

Radiology
Background Multimodality imaging is essential for personalized prognostic stratification in suspected coronary artery disease (CAD). Machine learning (ML) methods can help address this complexity by incorporating a broader spectrum of variables. Purp...

Automated proximal coronary artery calcium identification using artificial intelligence: advancing cardiovascular risk assessment.

European heart journal. Cardiovascular Imaging
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 ...