3 papers
eess.SP2025
Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for ECG Foundation Models
Giuliana Monachino, Nicolò La Porta, Beatrice Zanchi +4
Foundation Models (FMs) are large-scale machine learning models trained on extensive, diverse datasets that can be adapted to a wide range of downstream tasks with minimal fine-tun…
cs.LG2025
SLEEPYLAND: trust begins with fair evaluation of automatic sleep staging models
Alvise Dei Rossi, Matteo Metaldi, Michal Bechny +7
Despite advances in deep learning for automatic sleep staging, clinical adoption remains limited due to challenges in fair model evaluation, generalization across diverse datasets,…
stat.AP2025
Unveiling Sleep Dysregulation in Chronic Fatigue Syndrome with and without Fibromyalgia Through Bayesian Networks
Michal Bechny, Marco Scutari, Julia van der Meer +4
Chronic Fatigue Syndrome (CFS) and Fibromyalgia (FM) often co-occur as medically unexplained conditions linked to disrupted physiological regulation, including altered sleep. Build…