A Dual-input deep learning architecture for classification and latency estimation in ABR signals
Our findings highlight the promise of convolutional neural networks for enhancing ABR analysis and underscore their potential to streamline clinical workflows in the diagnosis of auditory disorders.
Authors
- Hasan F. Ateş (ORCID: https://orcid.org/0000-0002-6842-1528)
- Bahadır K. Güntürk (ORCID: https://orcid.org/0000-0003-0779-9620)
- Halil Berkay SALDIRIM (ORCID: https://orcid.org/0000-0003-1319-2008)
- Berna Özge Mutlu (ORCID: https://orcid.org/0000-0003-2013-7285)
- Oguz Yilmaz
- Youssef Darahem
Institutions
- Izmir University (TR)
- Istanbul Medipol University (TR)
- Özyeğin University (TR)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2025-11-11
- DOI
- https://doi.org/10.3389/fmed.2025.1693921
- Primary Topic
- ECG Monitoring and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Türkiye Bilimsel ve Teknolojik Araştırma Kurumu