loading...
From Mining Tinnitus Database to Tinnitus Decision-Support System, Initial Study
Silicon Valley, California, USA November 02-November 05
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/IAT.2007.882007 IEEE/WIC/ACM International Confe ...
 This Article 
 
PDF
HTML
 
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Many definitions for tinnitus exist and causes and treatments are plentiful, yet not completely understood. A database of eleven tables, as many as 555 unique patien tuples and numerous time-stamped and other features was obtained for knowledge discovery related to causes and treatments of tinnitus. The paper describes the knowledge discovery and machine learning process and introduces several new temporal features to improve tinnitus evaluation, outcomes analysis, and overall understanding. Through automated analysis it is the goal of the authors to determine unknown yet potentially useful attributes related to tinnitus research.
Citation:
Pamela Thompson, Xin Zhang, Wenxin Jiang, Zbigniew W. Ras, "From Mining Tinnitus Database to Tinnitus Decision-Support System, Initial Study," iat, pp.203-206, 2007 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT'07), 2007
Usage of this product signifies your acceptance of the Terms of Use.