Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/73742
Título: Use of data mining to predict significant factors and benefits of bilateral cochlear implantation
Autores/as: Ramos De Miguel, Ángel 
Perez-Zaballos, Teresa
Pérez Plasencia, Daniel 
Falcon, Juan Carlos
Ramos, Angel
Clasificación UNESCO: 32 Ciencias médicas
Palabras clave: Plasticity
Cochlear Implant
Bilateral
Quality Of Life
Data Mining
Fecha de publicación: 2015
Publicación seriada: European Archives of Oto-Rhino-Laryngology 
Resumen: Data mining (DM) is a technique used to discover pattern and knowledge from a big amount of data. It uses artificial intelligence, automatic learning, statistics, databases, etc. In this study, DM was successfully used as a predictive tool to assess disyllabic speech test performance in bilateral implanted patients with a success rate above 90 %. 60 bilateral sequentially implanted adult patients were included in the study. The DM algorithms developed found correlations between unilateral medical records and Audiological test results and bilateral performance by establishing relevant variables based on two DM techniques: the classifier and the estimation. The nearest neighbor algorithm was implemented in the first case, and the linear regression in the second. The results showed that patients with unilateral disyllabic test results below 70 % benefited the most from a bilateral implantation. Finally, it was observed that its benefits decrease as the inter-implant time increases.
URI: http://hdl.handle.net/10553/73742
ISSN: 0937-4477
DOI: 10.1007/s00405-014-3337-3
Fuente: European Archives of Oto-Rhino-Laryngology [ISSN 0937-4477], v. 272 (11), p. 3157-3162, (Noviembre 2015)
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