Abstract
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.
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Cyran, K.A. et al. (2013). Support Vector Machines in Biomedical and Biometrical Applications. In: Ramanna, S., Jain, L., Howlett, R. (eds) Emerging Paradigms in Machine Learning. Smart Innovation, Systems and Technologies, vol 13. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28699-5_15
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