A Novel end-to-end Digital Health System Using Deep Learning-based ECG Analysis
This study presents AI-HEART, a cloud-based information system for managing and analysing long-duration ambulatory electrocardiogram (ECG) recordings and supporting clinician decision-making. The platform operationalises an end-to-end pipeline that ingests multi-day three-lead ECGs, normalises inputs, performs signal preprocessing, and applies dedicated deep neural networks for wave delineation, noise/quality detection, and beat- and rhythm-level multi-class arrhythmia classification. To address class imbalance and real-world signal variability, model development combines large clinically annotated datasets with expert-in-the-loop curation and generative augmentation for under-represented...
| Authors | Artemis Kontou, Natalia Miroshnikova, Costakis Matheou et al. |
|---|---|
| Primary category | eess.SP |
| Published | 28 February 2026 |
| Last updated at source | 28 February 2026 |
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