Machine Learning to Characterize Speech Recognition and Quality of Life Outcomes in Adult Cochlear Implant Users
A battery of assessments can help characterize the profiles of CI users who experience favorable SR and QOL outcomes versus those who do not. This type of profiling analysis provides a potential tool for identifying individuals who are at high risk for experiencing poor SR and/or QOL outcomes, and those who may benefit from more specific counseling or rehabilitation.
Authors
- Ankita Patro (ORCID: https://orcid.org/0000-0001-8370-9071)
- Terrin N. Tamati (ORCID: https://orcid.org/0000-0003-1885-1877)
- Naweed I. Chowdhury (ORCID: https://orcid.org/0000-0001-9826-4917)
- Jaclyn Lee (ORCID: https://orcid.org/0000-0001-9804-6995)
- Aaron C. Moberly
Institutions
- Vanderbilt University Medical Center (US)
Publication Details
- Journal
- Otology & Neurotology
- Published
- 2026-03-11
- DOI
- https://doi.org/10.1097/mao.0000000000004839
- Primary Topic
- Hearing Loss and Rehabilitation
- Type
- article
- Field-Weighted Citation Impact
- 0.00