10 citations · 12 across the 5 of their papers we have counts for
5 papers
Learning transferable human physiology from two million hours of sleep with SleepFM-2
Rahul Thapa, Christopher Sun, William Theodor Lehn-Schioler +14
Sleep provides a nightly window into health by capturing coordinated activity across the brain, heart, muscles and respiratory system. We introduce SleepFM-2, a sleep foundation mo…
Agentic AI-enabled discovery across large-scale sleep physiology
Rahul Thapa, Umaer Hanif, Robin Guillard +10
Sleep occupies roughly one-third of human life, yet many aspects of its physiology remain poorly understood. Large polysomnography (PSG) datasets offer new opportunities to study s…
U-PASS: an Uncertainty-guided deep learning Pipeline for Automated Sleep Staging
Elisabeth R. M. Heremans, Nabeel Seedat, Bertien Buyse +3
As machine learning becomes increasingly prevalent in critical fields such as healthcare, ensuring the safety and reliability of machine learning systems becomes paramount. A key c…
L-SeqSleepNet: Whole-cycle Long Sequence Modelling for Automatic Sleep Staging
Huy Phan, Kristian P. Lorenzen, Elisabeth Heremans +7
Human sleep is cyclical with a period of approximately 90 minutes, implying long temporal dependency in the sleep data. Yet, exploring this long-term dependency when developing sle…
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…