Seoul National University · Medicine
Professor Yeonyee E. Yoon's research lab specializes in cardiovascular imaging, with a focus on echocardiography, cardiac magnetic resonance (CMR), and artificial intelligence (AI) applications in cardiac function assessment. The lab investigates left atrial mechanics, fibrosis, and remodeling in conditions such as atrial fibrillation, hypertrophic cardiomyopathy, and prediabetes, aiming to improve diagnostic accuracy and patient outcomes through advanced imaging techniques. A key research direction involves leveraging AI to reduce observer variability and enhance reproducibility in echocardiographic measurements.
Figures are computed from collected data and may differ slightly.
Patients with paroxysmal AF have decreased LA reservoir function and increased stiffness, in comparison with that of the control subjects. LA stiffness was significantly related with LA volume indices and reservoir function. LA stiffness can be used for the assessment of LA function in patients with paroxysmal AF.
Artificial intelligence (AI) is evolving in the field of diagnostic medical imaging, including echocardiography. Although the dynamic nature of echocardiography presents challenges beyond those of static images from X-ray, computed tomography, magnetic resonance, and radioisotope imaging, AI has influenced all steps of echocardiography, from image acquisition to automatic measurement and interpretation. Considering that echocardiography often is affected by inter-observer variability and shows a
Cardiac magnetic resonance (CMR) imaging is now widely used in several fields of cardiovascular disease assessment due to recent technical developments. CMR can give physicians information that cannot be found with other imaging modalities. However, there is no guideline which is suitable for Korean people for the use of CMR. Therefore, we have prepared a Korean guideline for the appropriate utilization of CMR to guide Korean physicians, imaging specialists, medical associates and patients to im
The presence of MI detected with late gadolinium-enhanced MR imaging is the strongest multivariable predictor of adverse cardiac events in patients with IFG. Late gadolinium-enhanced MR imaging may help identify a subpopulation of subjects in the prediabetic stage who may benefit from more intensive treatments.
HCM patients showed progressed LA remodeling and dysfunction; the determinant of LA remodeling and dysfunction was LV mass index rather than LV myocardial fibrosis by LGE-magnetic resonance imaging.
We evaluated whether breast arterial calcification (BAC) is associated with the progression of coronary atherosclerosis in asymptomatic women. This retrospective observational cohort study analysed asymptomatic women from the BBC registry. In 126 consecutive women (age, 54.5 ± 7.0 years) who underwent BAC evaluation and repeated coronary computed tomography angiography (CCTA) examinations, the coronary arterial calcification score (CACS) and segment stenosis score (SSS) were evaluated to assess
Triage of patients with acute, potentially life-threatening chest pain is one of the most important issues currently facing physicians in the emergency department. Appropriate evaluation of these patients begins with a skilled assessment of the individual patient's presenting symptoms and a careful review of his or her history and physical examination, often followed by serial recording of electrocardiograms and measurement of serum biochemical markers such as troponin and d-dimer. Stress testin
Patient-specific phenotyping of coronary atherosclerosis would facilitate personalized risk assessment and preventive treatment. We explored whether unsupervised cluster analysis can categorize patients with coronary atherosclerosis according to their plaque composition, and determined how these differing plaque composition profiles impact plaque progression. Patients with coronary atherosclerotic plaque (n = 947; median age, 62 years; 59% male) were enrolled from a prospective multi-national re
Open papers in the app to read, cite, and organize with AI.