AIMC Topic: Cardiovascular Diseases
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Association of retinal image-based, deep learning cardiac BioAge with telomere length and cardiovascular biomarkers.
Optometry and vision science : official publication of the American Academy of Optometry
Jun 28, 2024
SIGNIFICANCE: Our retinal image-based deep learning (DL) cardiac biological age (BioAge) model could facilitate fast, accurate, noninvasive screening for cardiovascular disease (CVD) in novel community settings and thus improve outcome with those wit...
Wearable ECG Device and Machine Learning for Heart Monitoring.
Sensors (Basel, Switzerland)
Jun 28, 2024
With cardiovascular diseases (CVD) remaining a leading cause of mortality, wearable devices for monitoring cardiac activity have gained significant, renewed interest among the medical community. This paper introduces an innovative ECG monitoring syst...
Prediction model for cardiovascular disease in patients with diabetes using machine learning derived and validated in two independent Korean cohorts.
Scientific reports
Jun 28, 2024
This study aimed to develop and validate a machine learning (ML) model tailored to the Korean population with type 2 diabetes mellitus (T2DM) to provide a superior method for predicting the development of cardiovascular disease (CVD), a major chronic...
[Artificial intelligence in cardiovascular radiology : Image acquisition, image reconstruction and workflow optimization].
Radiologie (Heidelberg, Germany)
Jun 24, 2024
BACKGROUND: Artificial intelligence (AI) has the potential to fundamentally change radiology workflow.
The role of artificial intelligence in cardiovascular magnetic resonance imaging.
Progress in cardiovascular diseases
Jun 24, 2024
Cardiovascular magnetic resonance (CMR) imaging is the gold standard test for myocardial tissue characterization and chamber volumetric and functional evaluation. However, manual CMR analysis can be time-consuming and is subject to intra- and inter-o...
The beating heart: artificial intelligence for cardiovascular application in the clinic.
Magma (New York, N.Y.)
Jun 22, 2024
Artificial intelligence (AI) integration in cardiac magnetic resonance imaging presents new and exciting avenues for advancing patient care, automating post-processing tasks, and enhancing diagnostic precision and outcomes. The use of AI significantl...
Innovative approaches for accurate ozone prediction and health risk analysis in South Korea: The combined effectiveness of deep learning and AirQ.
The Science of the total environment
Jun 21, 2024
Short-term exposure to ground-level ozone (O) poses significant health risks, particularly respiratory and cardiovascular diseases, and mortality. This study addresses the pressing need for accurate O forecasting to mitigate these risks, focusing on ...
Revolutionising Acute Cardiac Care With Artificial Intelligence: Opportunities and Challenges.
The Canadian journal of cardiology
Jun 18, 2024
This article reviews the application of artificial intelligence (AI) in acute cardiac care, highlighting its potential to transform patient outcomes in the face of the global burden of cardiovascular diseases. It explores how AI algorithms can rapidl...
Association of Cardiovascular Health With Brain Age Estimated Using Machine Learning Methods in Middle-Aged and Older Adults.
Neurology
Jun 18, 2024
BACKGROUND AND OBJECTIVES: Cardiovascular health (CVH) has been associated with cognitive decline and dementia, but the extent to which CVH affects brain health remains unclear. We investigated the association of CVH, assessed using Life's Essential ...
Perfect Match: Radiomics and Artificial Intelligence in Cardiac Imaging.
Circulation. Cardiovascular imaging
Jun 18, 2024
Cardiovascular diseases remain a significant health burden, with imaging modalities like echocardiography, cardiac computed tomography, and cardiac magnetic resonance imaging playing a crucial role in diagnosis and prognosis. However, the inherent he...
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