By Alexander Statnikov,Constantin F Aliferis,Douglas P Hardin
Support Vector Machines (SVMs) are one of the most vital fresh advancements in development acceptance and statistical computing device studying. they've got chanced on an outstanding variety of functions in numerous fields together with biology and medication. even if, biomedical researchers usually adventure problems greedy either the idea and functions of those vital equipment due to loss of technical heritage. the aim of this booklet is to introduce SVMs and their extensions and make allowance biomedical researchers to appreciate and observe them in real-life learn in an easy demeanour. The publication is to encompass volumes: concept and strategies (Volume 1) and case reports (Volume 2).
- Introduction and publication Overview
- Methods utilized in this Book
- Case stories and Comparative review 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 class (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 evaluate of Plasma Proteome Stability
- Case experiences and Comparative assessment in textual content Data:
- Application and comparability of SVMs and different tools for Retrieving fine quality Content-Specific Articles (Contributed by way of Yindalon Aphinyanaphongs)
- Application and comparability of SVMs and different tools for deciding on Unproven melanoma remedies on the internet (Contributed via Yindalon Aphinyanaphongs)
- Application to Predicting destiny Article Citations (Contributed via Lawrence Fu)
- Application to Classifying Instrumentality of Article Citations (Contributed via Lawrence Fu)
- Application and comparability of SVMs and different tools for choosing Drug–Drug Interactions-Related Literature (Contributed through Stephany Duda)
- Case reports with medical Data::
- Application to Predicting scientific Laboratory Values
- Application to Modeling scientific Judgment and guide Compliance within the prognosis of cancer (Contributed via 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 execs who wish to know about SVMs and correct bioinformatics instruments yet shouldn't have the required technical background.
Read or Download A Gentle Introduction to Support Vector Machines in Biomedicine:Volume 2: Case Studies and Benchmarks PDF
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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