This clinical trial focuses on testing the efficacy of different digital interventions to promote re-engagement in cancer-related long-term follow-up care for adolescent and young adult (AYA) survivors of childhood cancer.
The goal of the present study is to use computationally driven models of speech understanding in cochlear implant (CI) users to guide the search for which combination of active electrodes can yield the best speech understanding for a specific patient. It is hypothesized that model-recommended settings will result in significantly better speech understanding than standard-of-care settings.
A Computational Approach to Optimal Deactivation of Cochlear Implant Electrodes
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
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Sponsor: NYU Langone Health
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.