"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.
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| Year | Major Topic | Minor Topic | Total |
|---|
| 2013 | 0 | 1 | 1 |
| 2014 | 1 | 1 | 2 |
| 2015 | 0 | 1 | 1 |
| 2016 | 0 | 1 | 1 |
| 2019 | 0 | 1 | 1 |
| 2020 | 0 | 3 | 3 |
| 2021 | 0 | 1 | 1 |
| 2022 | 0 | 6 | 6 |
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Below are the most recent publications written about "Support Vector Machine" by people in Profiles.
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SCAI/ACR/APMA/SCVS/SIR/SVM/SVS/VESS Position Statement on Competencies for Endovascular Specialists Providing CLTI Care. Vasc Med. 2022 08; 27(4):405-414.
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SCAI/ACR/APMA/SCVS/SIR/SVM/SVS/VESS position statement on competencies for endovascular specialists providing CLTI care. J Vasc Surg. 2022 07; 76(1):25-34.
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Machine Learning and Image Processing Enabled Evolutionary Framework for Brain MRI Analysis for Alzheimer's Disease Detection. Comput Intell Neurosci. 2022; 2022:5261942.
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Improving mammography lesion classification by optimal fusion of handcrafted and deep transfer learning features. Phys Med Biol. 2022 02 21; 67(5).
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Applying Quantitative Radiographic Image Markers to Predict Clinical Complications After Aneurysmal Subarachnoid Hemorrhage: A Pilot Study. Ann Biomed Eng. 2022 Apr; 50(4):413-425.
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Applying a radiomics-based CAD scheme to classify between malignant and benign pancreatic tumors using CT images. J Xray Sci Technol. 2022; 30(2):377-388.
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End-to-End Neural Network for Feature Extraction and Cancer Diagnosis of In Vivo Fluorescence Lifetime Images of Oral Lesions. Annu Int Conf IEEE Eng Med Biol Soc. 2021 11; 2021:3894-3897.
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Machine learning prediction in cardiovascular diseases: a meta-analysis. Sci Rep. 2020 09 29; 10(1):16057.
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Comparison study of classification methods of intramuscular electromyography data for non-human primate model of traumatic spinal cord injury. Proc Inst Mech Eng H. 2020 Sep; 234(9):955-965.
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Gray matter volume and estimated brain age gap are not linked with sleep-disordered breathing. Hum Brain Mapp. 2020 08 01; 41(11):3034-3044.