BACKGROUND: The aim of this study was to evaluate the relationship between risk factors causing cardiovascular diseases and their importance with explainable machine learning models.
OBJECTIVE: Aortic stiffness and chronic kidney disease share common risk factors. Increased aortic stiffness is a predictor of lower estimated glomerular filtration rate (eGFR) at lower levels of renal functions. We aimed to investigate the associati...
OBJECTIVE: Cystatin C and neutrophil gelatinase-associated lipocalin (NGAL) are biomarkers of renal functions. We evaluated their roles in predicting the severity of coronary artery disease (CAD).
OBJECTIVE: Changes in left atrial (LA) function can be observed in type 1 diabetes mellitus (T1DM). Three-dimensional (3-D) speckle tracking echocardiography (STE) seems to be a promising tool for volumetric and functional evaluation of LA. The objec...
OBJECTIVE: Available evidence suggests that inflammation may be associated with atrial fibrillation (AF). This prospective and observational study aimed to assess whether plasma neopterin (NPT) and interleukin-6 (IL-6) levels before and after electri...
Artificial intelligence (AI) is being intensively applied to cardiology, particularly in diagnostics, risk prediction, treatment planning, and invasive procedures. While AI-driven advancements have demonstrated promise, their real-world implementatio...
Rapid development of artificial intelligence (AI) is gaining grounds in medicine. Its huge impact and inevitable necessity are also reflected in cardiovascular imaging. Although AI would probably never replace doctors, it can significantly support an...