Empirical comparison of deep ensembles and Monte Carlo dropout with GNLL and MSE losses, plus recalibration, shows DE and recalibrated GNLL perform best for predictive robustness and uncertainty calibration in PPG-based BP estimation under domain shift.
Vitaldb, a high-fidelity multi-parameter vital signs database in surgical patients.Scientific Data, 9(1):279, 2022
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Uncertainty Reliability Under Domain Shift: An Investigation for Data-Driven Blood Pressure Estimation in Photoplethysmography
Empirical comparison of deep ensembles and Monte Carlo dropout with GNLL and MSE losses, plus recalibration, shows DE and recalibrated GNLL perform best for predictive robustness and uncertainty calibration in PPG-based BP estimation under domain shift.