From Mining Tinnitus Database to Tinnitus Decision-Support System, Initial Study

Author

Thompson, Pamela ; Zhang, Xin ; Jiang, Wenxin ; Ras, Zbigniew W.

Author_Institution

Univ. of North Carolina, Charlotte

fYear

2007

fDate

2-5 Nov. 2007

Firstpage

203

Lastpage

206

Abstract

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 patient 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.

Keywords

data mining; database management systems; decision support systems; learning (artificial intelligence); medical information systems; knowledge discovery; machine learning process; tinnitus database mining; tinnitus decision-support system; tinnitus treatments; Autonomic nervous system; Computer science; Control systems; Data mining; Heart rate; Intelligent agent; Medical treatment; Nervous system; Relational databases; Spatial databases;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Agent Technology, 2007. IAT '07. IEEE/WIC/ACM International Conference on

Conference_Location

Fremont, CA

Print_ISBN

978-0-7695-3027-7

Type

conf

DOI

10.1109/IAT.2007.88

Filename

4407283