Self-supervised deep representation learning of a foundation transformer model enabling efficient ECG-based assessment of cardiac and coronary function with limited labels
Jonathan B. Moody,
Alexis Poitrasson-Rivière,
Jennifer M. Renaud
et al.
Abstract:Background: Impaired microvascular and vasomotor function is a common consequence of aging, diabetes, and other risk factors, and is associated with adverse cardiac outcomes. Such impairments are not readily identified by standard clinical methods of cardiovascular testing such as coronary angiography and noninvasive single photon emission tomography (SPECT) myocardial perfusion imaging (MPI). We hypothesized that signals embedded within stress electrocardiograms (ECGs) identify individuals with microvascular … Show more
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