Support Vector Machine

"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.

MeSH information

Definition | Details | More General Concepts | Related Concepts | More Specific Concepts

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".

Biological Sciences [G]
Mathematical Concepts [G17]
Algorithms [G17.035]
Artificial Intelligence [G17.035.250]
Machine Learning [G17.035.250.500]
Supervised Machine Learning [G17.035.250.500.500]
Support Vector Machine [G17.035.250.500.500.500]
Information Science [L]
Information Science [L01]
Computing Methodologies [L01.224]
Algorithms [L01.224.050]
Artificial Intelligence [L01.224.050.375]
Machine Learning [L01.224.050.375.530]
Supervised Machine Learning [L01.224.050.375.530.500]
Support Vector Machine [L01.224.050.375.530.500.500]

Below are MeSH descriptors whose meaning is related to "Support Vector Machine".

Below are MeSH descriptors whose meaning is more specific than "Support Vector Machine".

publications

Timeline | Most Recent

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.

Bar chart showing 7 publications over 6 distinct years, with a maximum of 2 publications in 2019

To see the data from this visualization as text, click here.

Year	Major Topic	Minor Topic	Total
2015	0	1	1
2017	0	1	1
2019	1	1	2
2020	1	0	1
2021	0	1	1
2022	1	0	1

Below are the most recent publications written about "Support Vector Machine" by people in Profiles.

Baurley JW, Claus ED, Witkiewitz K, McMahan CS. A Bayesian mixed effects support vector machine for learning and predicting daily substance use disorder patterns. Am J Drug Alcohol Abuse. 2022 Jul 04; 48(4):413-421.

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Gleichgerrcht E, Munsell BC, Alhusaini S, Alvim MKM, Bargalló N, Bender B, Bernasconi A, Bernasconi N, Bernhardt B, Blackmon K, Caligiuri ME, Cendes F, Concha L, Desmond PM, Devinsky O, Doherty CP, Domin M, Duncan JS, Focke NK, Gambardella A, Gong B, Guerrini R, Hatton SN, Kälviäinen R, Keller SS, Kochunov P, Kotikalapudi R, Kreilkamp BAK, Labate A, Langner S, Larivière S, Lenge M, Lui E, Martin P, Mascalchi M, Meletti S, O'Brien TJ, Pardoe HR, Pariente JC, Xian Rao J, Richardson MP, Rodríguez-Cruces R, Rüber T, Sinclair B, Soltanian-Zadeh H, Stein DJ, Striano P, Taylor PN, Thomas RH, Elisabetta Vaudano A, Vivash L, von Podewills F, Vos SB, Weber B, Yao Y, Lin Yasuda C, Zhang J, Thompson PM, Sisodiya SM, McDonald CR, Bonilha L. Artificial intelligence for classification of temporal lobe epilepsy with ROI-level MRI data: A worldwide ENIGMA-Epilepsy study. Neuroimage Clin. 2021; 31:102765.

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Kristinsson S, Zhang W, Rorden C, Newman-Norlund R, Basilakos A, Bonilha L, Yourganov G, Xiao F, Hillis A, Fridriksson J. Machine learning-based multimodal prediction of language outcomes in chronic aphasia. Hum Brain Mapp. 2021 04 15; 42(6):1682-1698.

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Fang H, Hui Q, Lynch J, Honerlaw J, Assimes TL, Huang J, Vujkovic M, Damrauer SM, Pyarajan S, Gaziano JM, DuVall SL, O'Donnell CJ, Cho K, Chang KM, Wilson PWF, Tsao PS, Sun YV, Tang H. Harmonizing Genetic Ancestry and Self-identified Race/Ethnicity in Genome-wide Association Studies. Am J Hum Genet. 2019 10 03; 105(4):763-772.

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Kim C, Zhu V, Obeid J, Lenert L. Natural language processing and machine learning algorithm to identify brain MRI reports with acute ischemic stroke. PLoS One. 2019; 14(2):e0212778.

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Del Gaizo J, Mofrad N, Jensen JH, Clark D, Glenn R, Helpern J, Bonilha L. Using machine learning to classify temporal lobe epilepsy based on diffusion MRI. Brain Behav. 2017 10; 7(10):e00801.

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Neely BA, Ferrante JA, Chaves JM, Soper JL, Almeida JS, Arthur JM, Gulland FM, Janech MG. Proteomic Analysis of Plasma from California Sea Lions (Zalophus californianus) Reveals Apolipoprotein E as a Candidate Biomarker of Chronic Domoic Acid Toxicosis. PLoS One. 2014; 10(4):e0123295.

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