Development of Machine-Learning Models for Tinnitus-Related Distress Classification Using Wavelet-Transformed Auditory Evoked Potential Signals and Clinical Data

Development of Machine-Learning Models for Tinnitus-Related Distress Classification Using Wavelet-Transformed Auditory Evoked Potential Signals and Clinical Data

Tinnitus is a highly prevalent condition, affecting more than 1 in 7 adults in the EU and causing negative effects on sufferers’ quality of life. In this study, we utilised data collected within the “UNITI” project, the largest EU tinnitus-related research programme. Initially, we extracted characte...

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Bibliographic Details
Main Authors: Ourania Manta, Michail Sarafidis, Winfried Schlee, Birgit Mazurek, George K. Matsopoulos, Dimitrios D. Koutsouris
Format: Article
Language:English
Published: MDPI AG 2023-06-01
Series:Journal of Clinical Medicine
Subjects:
tinnitus
auditory evoked potential
auditory brainstem response
auditory middle latency response
tinnitus-related distress
tinnitus handicap inventory
Online Access:https://www.mdpi.com/2077-0383/12/11/3843

Internet

https://www.mdpi.com/2077-0383/12/11/3843

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