COW: A co-evolving memetic wrapper for herb-herb interaction analysis in TCM informatics

1Citations
Citations of this article
3Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Traditional Chinese Medicine (TCM) relies heavily on interactions between herbs within prescribed formulae. However, given the combinatorial explosion due to the vast number of herbs available for treatment, the study of herb-herb interactions by pure human analysis is impractical, with computeraided analysis computationally expensive. Thus feature selection is crucial as a pre-processing step prior to herb-herb interaction analysis. In accord with this goal, a new feature selection algorithm known as a Co-evolving Memetic Wrapper (COW) is proposed: COW takes advantage of recent developments in genetic algorithms (GAs) and memetic algorithms (MAs), evolving appropriate feature subsets for a given domain. As part of preliminary research, COW is demonstrated to be effective in selecting herbs in the TCM insomnia datatset. Finally, possible future applications of COW are examined, both within TCM research and in broader data mining contexts. © 2012 Springer-Verlag.

Cite

CITATION STYLE

APA

Detterer, D., & Kwan, P. (2012). COW: A co-evolving memetic wrapper for herb-herb interaction analysis in TCM informatics. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7104 LNAI, pp. 361–371). https://doi.org/10.1007/978-3-642-28320-8_31

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free