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BioMed Research International
Volume 2014, Article ID 127572, 12 pages
http://dx.doi.org/10.1155/2014/127572
Research Article

Identifying Potential Clinical Syndromes of Hepatocellular Carcinoma Using PSO-Based Hierarchical Feature Selection Algorithm

Zhiwei Ji1 and Bing Wang1,2,3

1School of Electronics and Information Engineering, Tongji University, Shanghai 201804, China
2The Advanced Research Institute of Intelligent Sensing Network, Tongji University, Shanghai 201804, China
3The Key Laboratory of Embedded System and Service Computing, Tongji University, Ministry of Education, Shanghai 201804, China

Received 17 December 2013; Revised 7 February 2014; Accepted 10 February 2014; Published 17 March 2014

Academic Editor: Jose C. Nacher

Copyright © 2014 Zhiwei Ji and Bing Wang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Supplementary Material

Supplementary Materials: In this section, the detailed information of all the symptoms and syndromes were firstly described. In Table SS, each syndrome group and the symptoms which were arranged into the same group were presented. Table S1A-S1C, S2A-S2D, and S3A-S3G show the conditional probability tables of the Bayesian network "Emotion", "Cardiothoracic condition", and "Diet", respectively (Figure 6). As to the global network of all the 24 potential syndromes (Figure 7), all the conditional probability tables were presented in Table SS1-SS24.

  1. Supplementary Materials