By Alexander Statnikov,Constantin F Aliferis,Douglas P Hardin
Support Vector Machines (SVMs) are one of the most vital contemporary advancements in trend popularity and statistical laptop studying. they've got chanced on an exceptional variety of purposes in quite a few fields together with biology and drugs. despite the fact that, biomedical researchers frequently adventure problems greedy either the speculation and functions of those very important equipment as a result of loss of technical heritage. the aim of this publication is to introduce SVMs and their extensions and make allowance biomedical researchers to appreciate and practice them in real-life study in an easy demeanour. The publication is to encompass volumes: idea and techniques (Volume 1) and case stories (Volume 2).
- Introduction and ebook Overview
- Methods utilized in this Book
- Case experiences and Comparative evaluate 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 type (Contributed through Zhiguo Li)
- Application and comparability of SVMs and different equipment for Multicategory category in Microbiomics (Contributed through Mikael Henaff, Kranti Konganti, Varun Narendra, Alexander V Alekseyenko)
- Application to overview of Plasma Proteome Stability
- Case experiences and Comparative review in textual content Data:
- Application and comparability of SVMs and different tools for Retrieving high quality Content-Specific Articles (Contributed via Yindalon Aphinyanaphongs)
- Application and comparability of SVMs and different tools for picking out Unproven melanoma remedies on the internet (Contributed by means of Yindalon Aphinyanaphongs)
- Application to Predicting destiny Article Citations (Contributed through Lawrence Fu)
- Application to Classifying Instrumentality of Article Citations (Contributed via Lawrence Fu)
- Application and comparability of SVMs and different tools for settling on Drug–Drug Interactions-Related Literature (Contributed through Stephany Duda)
- Case stories with medical Data::
- Application to Predicting medical Laboratory Values
- Application to Modeling medical Judgment and instruction Compliance within the prognosis of cancer (Contributed by way of Andrea Sboner)
- Other Comparative evaluate reviews 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 want to know about SVMs and correct bioinformatics instruments yet wouldn't have the mandatory technical background.
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Additional 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