Deep Learning End-to-End Approach for the Prediction of Tinnitus based on EEG Data*

@article{Allgaier2021DeepLE,
  title={Deep Learning End-to-End Approach for the Prediction of Tinnitus based on EEG Data*},
  author={Johannes Allgaier and Patrick Neff and Winfried Schlee and Stefan Schoisswohl and R{\"u}diger Pryss},
  journal={2021 43rd Annual International Conference of the IEEE Engineering in Medicine \& Biology Society (EMBC)},
  year={2021},
  pages={816-819}
}
  • Johannes Allgaier, P. Neff, +2 authors Rüdiger Pryss
  • Published 1 November 2021
  • Computer Science, Medicine
  • 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
Tinnitus is attributed by the perception of a sound without any physical source causing the symptom. Symptom profiles of tinnitus patients are characterized by a large heterogeneity, which is a major obstacle in developing general treatments for this chronic disorder. As tinnitus patients often report severe constraints in their daily life, the lack of general treatments constitutes such a challenge that patients crave for any kind of promising method to cope with their tinnitus, even if it is… 

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