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The goal of the project is to develop an outcome prediction tool using machine learning approaches working on the largest integrated dataset ever investigated in the field of cochlear implants. The Medical School of Hannover (MHH) hosts the world’s largest CI center with almost 10,000 patients being implanted in Hannover until today and an increasing annual implantation rate of currently close to 600. Longitudinal hearing outcomes of these patients, comorbidities, imaging data and the according programming data of the devices are systematically stored or referenced in relational databases for more than 20 years, comprising millions of datasets. Moreover, it is already general practice that blood and perilymph samples are being taken from patients undergoing cochlear implantation with the aim to identify possible correlations between clinical data, genetic data, metabolomic data and audiological or etiological data. All these data shall be used in a data driven artificial intelligence-based approach to develop performance prediction tools for cochlear implant hearing outcomes to offer potential candidates a reliable prognosis of success and decide on the optimal treatment solution.

 

 

 

 

 

 

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