2 papers
cs.LG2025
Data distribution impacts the performance and generalisability of contrastive learning-based foundation models of electrocardiograms
Gul Rukh Khattak, Konstantinos Patlatzoglou, Joseph Barker +15
Contrastive learning is a widely adopted self-supervised pretraining strategy, yet its dependence on cohort composition remains underexplored. We present Contrasting by Patient Aug…
cs.LG2025
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements
Alexander Jenkins, Andrea Cini, Joseph Barker +10
Catheter ablation of Atrial Fibrillation (AF) consists of a one-size-fits-all treatment with limited success in persistent AF. This may be due to our inability to map the dynamics…