AIMC Topic: Coronary Disease
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Exploration of fractional flow reservation score based on artificial intelligence post-processing for coronary artery lesions in patients with diabetes and coronary heart disease.
SLAS technology
Sep 21, 2024
In order to evaluate the relationship between coronary heart disease (CHD) and fractional flow reservation (FFR) in patients with different levels of CHD and diabetes, this paper used AI (artificial intelligence) post-processing technology to detect ...
Predictive model and risk analysis for coronary heart disease in people living with HIV using machine learning.
BMC medical informatics and decision making
Apr 25, 2024
OBJECTIVE: This study aimed to construct a coronary heart disease (CHD) risk-prediction model in people living with human immunodeficiency virus (PLHIV) with the help of machine learning (ML) per electronic medical records (EMRs).
Diagnostic accuracy of artificial intelligence-enabled vectorcardiography versus myocardial perfusion SPECT in patients with suspected or known coronary heart disease.
Nuklearmedizin. Nuclear medicine
Feb 20, 2024
AIM: The present study evaluated with myocardial perfusion SPECT (MPS) the diagnostic accuracy of an artificial intelligence-enabled vectorcardiography system (Cardisiography, CSG) for detection of perfusion abnormalities.
Vascular Age Assessed From an Uncalibrated, Noninvasive Pressure Waveform by Using a Deep Learning Approach: The AI-VascularAge Model.
Hypertension (Dallas, Tex. : 1979)
Oct 30, 2023
BACKGROUND: Aortic stiffness, assessed as carotid-femoral pulse wave velocity, provides a measure of vascular age and risk for adverse cardiovascular disease outcomes, but it is difficult to measure. The shape of arterial pressure waveforms conveys i...
Precision epigenetics provides a scalable pathway for improving coronary heart disease care globally.
Epigenomics
Sep 13, 2023
Coronary heart disease (CHD) is the world's leading cause of death. Up to 90% of all CHD deaths are preventable, but effective prevention of this mortality requires more scalable, precise methods for assessing CHD status and monitoring treatment resp...
Association of retinal microvascular density and complexity with incident coronary heart disease.
Atherosclerosis
Jul 27, 2023
BACKGROUND AND AIMS: The high mortality rate and huge disease burden of coronary heart disease (CHD) highlight the importance of its early detection and timely intervention. Given the non-invasive nature of fundus photography and recent development i...
All-Cause Death Prediction Method for CHD Based on Graph Convolutional Networks.
Computational intelligence and neuroscience
Jul 18, 2022
Coronary heart disease (CHD) has become one of the most serious public health issues due to its high morbidity and mortality rates. Most of the existing coronary heart disease risk prediction models manually extract features based on shallow machine ...
Vessel segmentation for X-ray coronary angiography using ensemble methods with deep learning and filter-based features.
BMC medical imaging
Jan 19, 2022
BACKGROUND: Automated segmentation of coronary arteries is a crucial step for computer-aided coronary artery disease (CAD) diagnosis and treatment planning. Correct delineation of the coronary artery is challenging in X-ray coronary angiography (XCA)...
Prediction of coronary heart disease based on combined reinforcement multitask progressive time-series networks.
Methods (San Diego, Calif.)
Dec 23, 2021
Coronary heart disease is the first killer of human health. At present, the most widely used approach of coronary heart disease diagnosis is coronary angiography, a surgery that could potentially cause some physical damage to the patients, together w...
Association Between Coffee Intake and Incident Heart Failure Risk: A Machine Learning Analysis of the FHS, the ARIC Study, and the CHS.
Circulation. Heart failure
Feb 9, 2021
BACKGROUND: Coronary heart disease, heart failure (HF), and stroke are complex diseases with multiple phenotypes. While many risk factors for these diseases are well known, investigation of as-yet unidentified risk factors may improve risk assessment...
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