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|Title:||Data mining in biomedicine : current applications and further directions for research|
|Authors:||Ting, S. L.|
Shum, C. C.
Kwok, Siu Keung
Tsang, Albert H. C.
Lee, W. B.
|Publisher:||Scientific Research Publishing|
|Source:||Journal of software engineering and applications, Oct. 2009, v. 2, no. 3, p. 150-159.|
|Abstract:||Data mining is the process of finding the patterns, associations or relationships among data using different analytical techniques involving the creation of a model and the concluded result will become useful information or knowledge. The advancement of the new medical deceives and the database management systems create a huge number of data-bases in the biomedicine world. Establishing a methodology for knowledge discovery and management of the large amounts of heterogeneous data has become a major priority of research. This paper introduces some basic data mining techniques, unsupervised learning and supervising learning, and reviews the application of data mining in biomedicine. Applications of the multimedia mining, including text, image, video and web mining are discussed. The key issues faced by the computing professional, medical doctors and clinicians are highlighted. We also state some foreseeable future developments in the field. Although extracting useful information from raw biomedical data is a challenging task, data mining is still a good area of scientific study and remains a promising and rich field for research.|
|Rights:||Copyright © 2009 SciRes|
Journal of software engineering and applications is available online at: http://www.scirp.org/journal/jsea. This is a postprint of an article. The definitive, peer-reviewed and edited version of this article is published in Journal of software engineering and applications, v. 2, no. 3, p. 150-159, doi: 10.4236/jsea.2009.23022.
|Appears in Collections:||COMP Journal/Magazine Articles|
ISE Journal/Magazine Articles
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