Journal: Scientific Reports
Article Title: Validation of AI-enhanced ECG image analysis for identifying extreme cardiac magnetic resonance metrics in a cross-ethnic UK biobank study
doi: 10.1038/s41598-026-41824-5
Figure Lengend Snippet: Flowchart illustrating AI-ECG algorithm development and validation dataset. The six AI-ECG models used in this study s– four targeting functional abnormalities and two targeting structural abnormalities – were previously developed using ECG datasets from Seoul National University Bundang Hospital (SNUBH). These models were validated against CMR-derived values in the UK Biobank population. CMR = cardiac magnetic resonance imaging, ECG electrocardiography, QCG quantitative ECG, LVD left ventricular dysfunction, RVD right ventricular dysfunction, GLS global longitudinal strain, LVH left ventricular hypertrophy, LAE left atrial enlargement.
Article Snippet: CMR imaging in the UK Biobank was conducted using 1.5-Tesla MAGNETOM Aera scanners (Siemens Healthcare, Syngo Platform VD13A), following a previously established protocol .
Techniques: Biomarker Discovery, Functional Assay, Derivative Assay, Magnetic Resonance Imaging