ArticleNPJ digital medicine2024
AI-enhanced reconstruction of the 12-lead electrocardiogram via 3-leads with accurate clinical assessment.
Article in NPJ digital medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- I-GraphECG: Observability-Based Lead Selection and Interpretable Disease Prediction from the 12-Lead ECG Using a Gray-Box Graph Electrophysiology Surrogate.Sensors (Basel, Switzerland) · 2026Article
- Anti-aliasing-enhanced WaveUNet for clinically reliable 12-lead ECG reconstruction from limited 3-lead input.Medical & biological engineering & computing · 2026Article
- Reconstructing 12-lead ECG from 3-lead ECG using variational autoencoder to improve cardiac disease detection of wearable ECG devices.PLOS digital health · 2026Article
- Artificial Intelligence Powered Wearable and Portable Devices for Remote Cardiac Care and Population Health.Current cardiology reports · 2026Review
- Integration of clinical data with scanned ECGs using deep learning methods for stroke risk prediction in Indian patients with atrial fibrillation: evidence from the KERALA-AF study.The Lancet regional health. Southeast Asia · 2026Article
- On the redundancy of denoising in electrocardiogram reconstruction.Frontiers in cardiovascular medicine · 2026Article
- Handheld 6-Lead ECG for Early Detection of Acute Inferior Wall ST-T Segment Elevation Myocardial Infarction: HINT-MI Study Design and Rationale.Medicina (Kaunas, Lithuania) · 2024Observational
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Authors and funding
6 authors.
Funding
Abstract
The 12-lead electrocardiogram (ECG) is an integral component to the diagnosis of a multitude of cardiovascular conditions. It is performed using a complex set of skin surface electrodes, limiting its use outside traditional clinical settings. We developed an artificial intelligence algorithm, trained over 600,000 clinically acquired ECGs, to explore whether fewer leads as input are sufficient to reconstruct a 12-lead ECG. Two limb leads (I and II) and one precordial lead (V3) were required to generate a reconstructed 12-lead ECG highly correlated with the original ECG. An automatic algorithm for detection of ECG features consistent with acute myocardial infarction (MI) performed similarly for original and reconstructed ECGs (AUC = 0.95). When interpreted by cardiologists, reconstructed ECGs achieved an accuracy of 81.4 ± 5.0% in identifying ECG features of ST-segment elevation MI, comparable with the original 12-lead ECGs (accuracy 84.6 ± 4.6%). These results will impact development efforts to innovate ECG acquisition methods with simplified tools in non-specialized settings.
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Registered trials
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