"Support Vector Machine" is a descriptor in the National Library of Medicine's controlled vocabulary thesaurus,
MeSH (Medical Subject Headings). Descriptors are arranged in a hierarchical structure,
which enables searching at various levels of specificity.
SUPERVISED MACHINE LEARNING algorithm which learns to assign labels to objects from a set of training examples. Examples are learning to recognize fraudulent credit card activity by examining hundreds or thousands of fraudulent and non-fraudulent credit card activity, or learning to make disease diagnosis or prognosis based on automatic classification of microarray gene expression profiles drawn from hundreds or thousands of samples.
| Descriptor ID |
D060388
|
| MeSH Number(s) |
G17.035.250.500.500.500 L01.224.050.375.530.500.500
|
| Concept/Terms |
Support Vector Machine- Support Vector Machine
- Machine, Support Vector
- Machines, Support Vector
- Support Vector Machines
- Vector Machine, Support
- Vector Machines, Support
Support Vector Network- Support Vector Network
- Network, Support Vector
- Networks, Support Vector
- Support Vector Networks
- Vector Network, Support
- Vector Networks, Support
|
Below are MeSH descriptors whose meaning is more general than "Support Vector Machine".
Below are MeSH descriptors whose meaning is more specific than "Support Vector Machine".
This graph shows the total number of publications written about "Support Vector Machine" by people in this website by year, and whether "Support Vector Machine" was a major or minor topic of these publications.
To see the data from this visualization as text,
click here.
| Year | Major Topic | Minor Topic | Total |
|---|
| 2012 | 0 | 1 | 1 |
| 2016 | 0 | 1 | 1 |
| 2017 | 8 | 9 | 17 |
| 2018 | 3 | 18 | 21 |
| 2019 | 5 | 1 | 6 |
| 2020 | 0 | 3 | 3 |
| 2021 | 3 | 4 | 7 |
To return to the timeline, click here.
Below are the most recent publications written about "Support Vector Machine" by people in Profiles.
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Accurate detection of COVID-19 using deep features based on X-Ray images and feature selection methods. Comput Biol Med. 2021 10; 137:104771.
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Computational predictions for protein sequences of COVID-19 virus via machine learning algorithms. Med Biol Eng Comput. 2021 Sep; 59(9):1723-1734.
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Support Vector Machine as a Supervised Learning for the Prioritization of Novel Potential SARS-CoV-2 Main Protease Inhibitors. Int J Mol Sci. 2021 Jul 19; 22(14).
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A machine learning based exploration of COVID-19 mortality risk. PLoS One. 2021; 16(7):e0252384.
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Predication of oxygen requirement in COVID-19 patients using dynamic change of inflammatory markers: CRP, hypertension, age, neutrophil and lymphocyte (CHANeL). Sci Rep. 2021 06 22; 11(1):13026.
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COVID-19 cough classification using machine learning and global smartphone recordings. Comput Biol Med. 2021 08; 135:104572.
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Assessment of protein-protein interfaces in cryo-EM derived assemblies. Nat Commun. 2021 06 07; 12(1):3399.
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Covid-19 diagnosis by combining RT-PCR and pseudo-convolutional machines to characterize virus sequences. Sci Rep. 2021 06 02; 11(1):11545.
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Quantum Machine Learning Algorithms for Drug Discovery Applications. J Chem Inf Model. 2021 06 28; 61(6):2641-2647.
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Gene selection using hybrid dragonfly black hole algorithm: A case study on RNA-seq COVID-19 data. Anal Biochem. 2021 Aug 15; 627:114242.