348 citations · 504 across the 15 of their papers we have counts for
16 papers
Improving Multimodal Learning with Multi-Loss Gradient Modulation
Konstantinos Kontras, Christos Chatzichristos, Matthew Blaschko +1
Learning from multiple modalities, such as audio and video, offers opportunities for leveraging complementary information, enhancing robustness, and improving contextual understand…
Personalized Longitudinal Assessment of Multiple Sclerosis Using Smartphones
Oliver Y. Chén, Florian Lipsmeier, Huy Phan +5
Personalized longitudinal disease assessment is central to quickly diagnosing, appropriately managing, and optimally adapting the therapeutic strategy of multiple sclerosis (MS). I…
Feature matching as improved transfer learning technique for wearable EEG
Elisabeth R. M. Heremans, Huy Phan, Amir H. Ansari +4
Objective: With the rapid rise of wearable sleep monitoring devices with non-conventional electrode configurations, there is a need for automated algorithms that can perform sleep…
SleepTransformer: Automatic Sleep Staging with Interpretability and Uncertainty Quantification
Huy Phan, Kaare Mikkelsen, Oliver Y. Chén +3
Background: Black-box skepticism is one of the main hindrances impeding deep-learning-based automatic sleep scoring from being used in clinical environments. Methods: Towards inter…
Light-weight sleep monitoring: electrode distance matters more than placement for automatic scoring
Kaare B. Mikkelsen, Huy Phan, Mike L. Rank +3
Modern sleep monitoring development is shifting towards the use of unobtrusive sensors combined with algorithms for automatic sleep scoring. Many different combinations of wet and…
Interpretable Deep Learning for the Remote Characterisation of Ambulation in Multiple Sclerosis using Smartphones
Andrew P. Creagh, Florian Lipsmeier, Michael Lindemann +1
The emergence of digital technologies such as smartphones in healthcare applications have demonstrated the possibility of developing rich, continuous, and objective measures of mul…