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Mining Tinnitus Database for Knowledge
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Author(s): Pamela L. Thompson (University of North Carolina at Charlotte, USA), Xin Zhang (University of North Carolina at Pembroke, USA), Wenxin Jiang (University of North Carolina at Charlotte, USA), Zbigniew W. Ras (University of North Carolina at Charlotte, USA)and Pawel Jastreboff (Emory University School of Medicine, USA)
Copyright: 2009
Pages: 14
Source title:
Data Mining and Medical Knowledge Management: Cases and Applications
Source Author(s)/Editor(s): Petr Berka (University of Economics, Prague, Czech Republic), Jan Rauch (University of Economics, Prague, Czech Republic)and Djamel Abdelkader Zighed (University of Lumiere Lyon 2, France)
DOI: 10.4018/978-1-60566-218-3.ch014
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Abstract
This chapter describes the process used to mine a database containing data, related to patient visits during Tinnitus Retraining Therapy. The original collection of datasets containing diagnostic and treatment data on tinnitus patients and visits was collected by P. Jastreboff. This sparse dataset consisted of eleven tables primarily related by patient id, number, and date of visit. First, with the help of P. Jastreboff, we gained an understanding of the domain knowledge spanning different disciplines (including otology and audiology), and then we used this knowledge to extract, transform, and mine the constructed database. Complexities were encountered with temporal data and text mining of certain features.The researchers focused on analysis of existing data, along with automating the discovery of new and useful features in order to improve classification and understanding of tinnitus diagnosis.
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