Beyond MIT-BIH: Failure Modes of Beat-Level ECG Arrhythmia Classification at Scale
A. Nicolson, R. Lunelli, Samuel Martin Pr ̈oll et al.
· 0 citations
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AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Open access
Sep 2026
BenchECG and xECG: a benchmark and baseline for ECG foundation models
Electrocardiograms (ECGs) are inexpensive, widely used, and well-suited to deep learning. Interest has grown in ECG foundation models that generalise across diverse downstream tasks. However, current evaluation rarely reflects the full capabilities expected of ECG foundation models, with prior work often using narrow...
R. Lunelli, A. Nicolson, S. Pröll et al.
· npj Digital Medicine · 0 citations
Open access
Jul 2026
Artificial intelligence-based ECG reconstruction error as a continuous predictor of all-cause mortality: a multi-cohort retrospective validation study
This work aimed to develop a self-supervised AI-ECG risk score based on the error in reconstructing a partially masked ECG, providing a direct measure of how much each recording deviates from normal cardiac electrical patterns.
A. Nicolson, S. ProÌll, R. Lunelli et al.
· medRxiv · 0 citations