By Alexander Statnikov,Constantin F Aliferis,Douglas P Hardin
Support Vector Machines (SVMs) are one of the most vital fresh advancements in trend attractiveness and statistical laptop studying. they've got came upon an excellent variety of purposes in a number of fields together with biology and drugs. besides the fact that, biomedical researchers frequently event problems greedy either the idea and purposes of those very important equipment as a result of loss of technical heritage. the aim of this ebook is to introduce SVMs and their extensions and make allowance biomedical researchers to appreciate and follow them in real-life examine in an easy demeanour. The e-book is to encompass volumes: concept and techniques (Volume 1) and case experiences (Volume 2).
- Introduction and ebook Overview
- Methods utilized in this Book
- Case stories and Comparative overview in High-Throughput Genomic Data:
- Application and comparability of SVMs and different equipment for Multicategory Microarray-Based melanoma Classification
- Comparison of SVMs and Random Forests for Microarray-Based melanoma Classification
- Comparison of SVMs and Kernel Ridge Regression for Microarray-Based melanoma category (Contributed via Zhiguo Li)
- Application and comparability of SVMs and different tools for Multicategory category in Microbiomics (Contributed through Mikael Henaff, Kranti Konganti, Varun Narendra, Alexander V Alekseyenko)
- Application to evaluate of Plasma Proteome Stability
- Case stories and Comparative review in textual content Data:
- Application and comparability of SVMs and different tools for Retrieving top of the range Content-Specific Articles (Contributed by way of Yindalon Aphinyanaphongs)
- Application and comparability of SVMs and different tools for settling on Unproven melanoma remedies on the internet (Contributed via Yindalon Aphinyanaphongs)
- Application to Predicting destiny Article Citations (Contributed by means of Lawrence Fu)
- Application to Classifying Instrumentality of Article Citations (Contributed through Lawrence Fu)
- Application and comparability of SVMs and different tools for choosing Drug–Drug Interactions-Related Literature (Contributed through Stephany Duda)
- Case reports with scientific Data::
- Application to Predicting scientific Laboratory Values
- Application to Modeling scientific Judgment and instruction Compliance within the prognosis of cancer (Contributed through Andrea Sboner)
- Other Comparative evaluate reports of extensive Applicability:
- Using SVMs for Causal Variable Selection
- Application and comparability of SVM-RFE and GLL Methods
Readership: Biomedical researchers and healthcare pros who wish to find out about SVMs and suitable bioinformatics instruments yet wouldn't have the required technical background.
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Extra resources for A Gentle Introduction to Support Vector Machines in Biomedicine:Volume 2: Case Studies and Benchmarks
A Gentle Introduction to Support Vector Machines in Biomedicine:Volume 2: Case Studies and Benchmarks by Alexander Statnikov,Constantin F Aliferis,Douglas P Hardin