Harnessing Machine Learning for Personalized Care of Idiopathic Sudden Sensorineural Hearing Loss: A Multicenter Cohort Study
The machine-learning-based prediction model enables personalized strategies and timely adjustments of treatment for ISSNHL, optimizing the likelihood of complete recovery.
Authors
- Ching‐Ting Tan (ORCID: https://orcid.org/0000-0001-8317-2235)
- Tzu-Hsiang Yang
- Pey‐Yu Chen (ORCID: https://orcid.org/0000-0002-4711-7818)
- Ting-Yi Lee
- Chen‐Chi Wu (ORCID: https://orcid.org/0000-0002-5047-2204)
- Yen-Ting Guo
- Tien‐Chen Liu (ORCID: https://orcid.org/0000-0001-6771-5025)
- Pei‐Hsuan Lin (ORCID: https://orcid.org/0000-0002-0855-5559)
- Chunying Wang (ORCID: https://orcid.org/0000-0002-6554-1188)
- Ting-Hua Yang
- Cheng Huang (ORCID: https://orcid.org/0000-0002-7149-9879)
Institutions
- National Taiwan University (TW)
- Mackay Memorial Hospital (TW)
- Mackay Medical University (TW)
- Quanta Computer (Taiwan) (TW)
- National Taiwan University Hospital (TW)
Publication Details
- Journal
- Clinical and Experimental Otorhinolaryngology
- Published
- 2025-12-02
- DOI
- https://doi.org/10.21053/ceo.2025-00084
- Primary Topic
- Vestibular and auditory disorders
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Taiwan University Hospital
- National Taiwan University