Support Vector Machines in Biomedical and Biometrical Applications

  • Krzysztof A. Cyran
  • Jolanta Kawulok
  • Michal Kawulok
  • Magdalena Stawarz
  • Marcin Michalak
  • Monika Pietrowska
  • Piotr Widłak
  • Joanna Polańska
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 13)


In the chapter, a background review material concerning applications of the kernel methods in computational biology and biometry is illustrated by the case studies concerning the proteomic spectra analysis to find diagnostic biomarkers and performing case-control discrimination as well as the face recognition problem, which is situated among the most investigated biometric methods. These case studies, representing the state-of-the-art in applications of the support vector machines (SVM) in biomedical and biometrical applications, are the examples of a research work conducted by computer scientists, bioinformaticians, and biostatisticians from the Faculty of Automatic Control, Electronics and Computer Science at Silesian University of Technology in a collaboration with clinicists from the Institute of Oncology in Gliwice, Poland.


Support Vector Machine Face Recognition Support Vector Regression Face Detection Feature Extraction Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Krzysztof A. Cyran
    • 1
  • Jolanta Kawulok
    • 1
  • Michal Kawulok
    • 1
  • Magdalena Stawarz
    • 1
  • Marcin Michalak
    • 1
  • Monika Pietrowska
    • 2
  • Piotr Widłak
    • 2
  • Joanna Polańska
    • 3
  1. 1.Institute of InformaticsGliwicePoland
  2. 2.Institute of OncologyGliwicePoland
  3. 3.Institute of Automatic ControlGliwicePoland

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