Gentle Introduction To Support Vector Machines In Biomedicine, A - Volume 2

Preliminaries: Introduction and Book Overview; Methods Used in this Book; Case Studies and Comparative Evaluation in High-Throughput Genomic Data: Application and Comparison of SVMs and Other Methods for Multicategory Microarray-Based Cancer Classification; Comparison of SVMs and Random Forests for Microarray-Based Cancer Classification; Comparison of SVMs and Kernel Ridge Regression for Microarray-Based Cancer Classification (Contributed by Zhiguo Li); Application and Comparison of SVMs and Other Methods for Multicategory Classification in Microbiomics (Contributed by Mikael Henaff, Kranti Konganti, Varun Narendra, Alexander V Alekseyenko); Application to Assessment of Plasma Proteome Stability; Case Studies and Comparative Evaluation in Text Data: Application and Comparison of SVMs and Other Methods for Retrieving High-Quality Content-Specific Articles (Contributed by Yindalon Aphinyanaphongs); Application and Comparison of SVMs and Other Methods for Identifying Unproven Cancer Treatments on the Web (Contributed by Yindalon Aphinyanaphongs); Application to Predicting Future Article Citations (Contributed by Lawrence Fu); Application to Classifying Instrumentality of Article Citations (Contributed by Lawrence Fu); Application and Comparison of SVMs and Other Methods for Identifying Drug - Drug Interactions-Related Literature (Contributed by Stephany Duda); Case Studies with Clinical Data: Application to Predicting Clinical Laboratory Values; Application to Modeling Clinical Judgment and Guideline Compliance in the Diagnosis of Melanoma (Contributed by Andrea Sboner); Other Comparative Evaluation Studies of Broad Applicability: Using SVMs for Causal Variable Selection; Application and Comparison of SVM-RFE and GLL Methods.