3 papers
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,…
eess.SP2024
Comparison analysis between standard polysomnographic data and in-ear-EEG signals: A preliminary study
Gianpaolo Palo, Luigi Fiorillo, Giuliana Monachino +8
Study Objectives: Polysomnography (PSG) currently serves as the benchmark for evaluating sleep disorders. Its discomfort makes long-term monitoring unfeasible, leading to bias in s…
cs.LG2023
Bridging AI and Clinical Practice: Integrating Automated Sleep Scoring Algorithm with Uncertainty-Guided Physician Review
Michal Bechny, Giuliana Monachino, Luigi Fiorillo +5
Purpose: This study aims to enhance the clinical use of automated sleep-scoring algorithms by incorporating an uncertainty estimation approach to efficiently assist clinicians in t…