The NEXT-GEN-SOMNUS (Next Generation Machine Learning Algorithms for the Analysis of Medical Sleep Recordings) project targets the improvement of the state-of-the-art related to the computational analysis of polysomnographic sleep recordings through the development of comprehensive, robust, generalizable, and interpretable solutions based on next-generation machine learning techniques. Among others, the project investigates the applicability and integration of novel self-attention mechanisms, "human-in-the-loop" techniques, and possible contributions of quantum machine learning.
This is the collection of scientific publications, software libraries and other materials created by the project consortium.
Research supported by project PID2023-147422OB-I00, funded by MCIU/AEI/10.13039/501100011033 and by European FEDER program.