Developing a diagnostic support system for audiogram interpretation using deep learning-based object detection
Our proposed automated approach for audiogram digitization and hearing loss classification performs comparably to traditional methods and otolaryngologists' interpretations. This system can potentially assist otolaryngologists in providing more timely and effective treatment by quickly and accurately classifying hearing loss.
Authors
- Kanokrat Bunnag (ORCID: https://orcid.org/0000-0001-6584-9476)
- Titipat Achakulvisut (ORCID: https://orcid.org/0000-0002-2124-2979)
- Sirinan Junthong (ORCID: https://orcid.org/0000-0002-0056-9577)
- Suchanon Phanthong
- Thanawut Timpitak
- Kanpat Vesessook
- Withita Utainrat
Institutions
- Mahidol University (TH)
- Navamindradhiraj University (TH)
- Bangkok University (TH)
Publication Details
- Journal
- Journal of Otology
- Published
- 2025-01-01
- DOI
- https://doi.org/10.26599/joto.2025.9540005
- Primary Topic
- Speech and Audio Processing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Mahidol University