Generalizable Sample-Efficient Siamese Autoencoder for Tinnitus Diagnosis in Listeners With Subjective Tinnitus

Electroencephalogram (EEG)-based neurofeedback has been widely studied for tinnitus therapy in recent years. Most existing research relies on experts' cognitive prediction, and studies based on machine learning and deep learning are either data-hungry or not well generalizable to new subjects....

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Vydané v:	IEEE transactions on neural systems and rehabilitation engineering Ročník 29; s. 1452 - 1461
Hlavní autori:	Liu, Zhe, Yao, Lina, Wang, Xianzhi, Monaghan, Jessica J. M., Schaette, Roland, He, Zihuai, McAlpine, David
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Ablation Algorithms Auditory system Brain modeling Coders Cognitive ability Deep learning domain alignment EEG Electroencephalography Encoders-Decoders Feature extraction Feedback Fineness Learning algorithms Machine learning Medical diagnosis Medical treatment Neurofeedback Predictive control siamese autoencoder subject-independent Tinnitus Training trend descriptor
ISSN:	1534-4320, 1558-0210, 1558-0210
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