Biomarker discovery is an important area of biomedical research that may lead to significant breakthroughs in disease analysis and targeted therapy. Biomarkers are biological entities whose alterations are measurable and are characteristic of a particular biological condition. Discovering, managing, and interpreting knowledge of new biomarkers are challenging and attractive problems in the emerging field of biomedical informatics.
This volume?is a collection of state-of-the-art?research into the application of data mining to the discovery and analysis of new biomarkers. Presenting new results, models and algorithms, the included contributions focus on biomarker data integration, information retrieval methods, and statistical machine learning techniques.
This volume is intended for students, and researchers in bioinformatics, proteomics, and genomics, as well?engineers and applied scientists?interested in the interdisciplinary application of data mining techniques.
This book applies data mining techniques to the discovery and analysis of new biomarkers. Presenting new results, models and algorithms, coverage focuses on biomarker data integration, information retrieval methods and statistical machine learning techniques.
Preface.- 1. Data Mining Strategies Applied in Brain Injury Models (S. Mondello, F. Kobeissy, I. Fingers, Z. Zhang, R.L. Hayes, K.K.W. Wang).- Application of Decomposition Methods in the Filtering of Event Related Potentials (K. Michalopoulos, V. Iordanidou, M. Zervakis).- 3. EEG Features as Biomarkers for Discrimination of Pre-ictal states (A. Tsimpiris, D. Kugiumtzis).- 4. Using Relative Power Asymmetry as a Biomarker for Classifying Psychogenic Non-epileptic Seizure and Complex Partial Seizure Patients (J.H. Chien, D.-S. Shiau, J.C. Sackellares, J.J. Halford, K.M. Kelly, P.M. Pardalos).- 5. Classification of Tree and Network Topology Structures in Medical Images (A. Skoura, V. MegalooikolCİ
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