Artificial Intelligence in Medicine
Volume 48, Issue 2 , Pages 71-73 , February 2010

Artificial intelligence in biomedical engineering and informatics: An introduction and review

  • Yonghong Peng

      Affiliations

    • Department of Computing, University of Bradford, West Yorkshire, BD7 1DP, UK
    • Corresponding Author InformationCorresponding author. Tel.: +44 1274 233963; fax: +44 1274 233920.
  • Yufeng Zhang

      Affiliations

    • Department of Electronic Engineering, Yunnan University, 650091, China
  • Lipo Wang

      Affiliations

    • School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, 50 Nanyang Avenue, 639798, Singapore

References 

  1. Antoniadis A, Lambert-Lacroix S, Leblanc F. Effective dimension reduction methods for tumor classification using gene expression data. Bioinformatics. 2003;19(5):563–570
  2. Guyon I, Weston J, Barnhill S, Vapnik V. Gene selection for cancer classification using support vector machines. Mach Learn. 2002;46:389–422
  3. Wang M, Chen JY. A GMM-IG framework for selecting genes as expression panel biomarkers. Artif Intell Med. 2010;48:75–82
  4. Kim G, Kim Y, Lim H, Kim H. An MLP-based feature subset selection for HIV-1 protease cleavage site analysis. Artif Intell Med. 2010;48:83–89
  5. Xu R, Damelin S, Nadler B, Wunsch DC. Clustering of high-dimensional gene expression data with feature filtering methods and diffusion maps. Artif Intell Med. 2010;48:91–98
  6. Sun J, Han L, Zhao Z. Gene- and evidence-based candidate gene selection for schizophrenia and gene feature analysis. Artif Intell Med. 2010;48:99–106
  7. Tsay J, Wu B, Jeng Y. Hierarchically organized layout for visualization of biochemical pathways. Artif Intell Med. 2010;48:107–117
  8. Wang HQ, Zhu HL, Cho WCS, Yip TTC, Ngan RKC, Low SCK. Method of regulatory network that can explore protein regulations for disease classification. Artif Intell Med. 2010;48:119–127
  9. Zeng T, Liu J. Mixture classification model based on clinical markers for breast cancer prognosis. Artif Intell Med. 2010;48:129–137
  10. Zhou X, Chen S, Liu B, Zhang R, Wang Y, Li P, et al. Development of traditional Chinese medicine clinical data warehouse for medical knowledge discovery and decision support. Artif Intell Med. 2010;48:139–152
  11. Barabasi AL, Oltvai ZN. Network biology: understanding the cell's functional organization. Nature Reviews Genetics. 2004;5(2):101–113
  12. Zhang S, Ching W, Tsing N, Leung H. A new multiple regression approach for the construction of genetic regulatory networks. Artif Intell Med. 2010;48:153–160
  13. Lin S, Xiao K, Huang Y, Chiu C, Soo V. Analysis of adverse drug reactions using drug and drug target interactions and graph-based methods. Artif Intell Med. 2010;48:161–166

PII: S0933-3657(09)00098-0

doi: 10.1016/j.artmed.2009.07.007

Artificial Intelligence in Medicine
Volume 48, Issue 2 , Pages 71-73 , February 2010