Supervised Machine Learning
"Supervised Machine Learning" 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.
A MACHINE LEARNING paradigm used to make predictions about future instances based on a given set of labeled paired input-output training (sample) data.
| Descriptor ID |
D000069553
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| MeSH Number(s) |
G17.035.250.500.500 L01.224.050.375.530.500
|
| Concept/Terms |
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Below are MeSH descriptors whose meaning is more general than "Supervised Machine Learning".
Below are MeSH descriptors whose meaning is more specific than "Supervised Machine Learning".
This graph shows the total number of publications written about "Supervised Machine Learning" by people in this website by year, and whether "Supervised Machine Learning" was a major or minor topic of these publications.
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| Year | Major Topic | Minor Topic | Total |
|---|
| 2016 | 1 | 0 | 1 |
| 2018 | 1 | 2 | 3 |
| 2019 | 0 | 1 | 1 |
| 2020 | 1 | 0 | 1 |
| 2021 | 1 | 0 | 1 |
| 2023 | 0 | 1 | 1 |
| 2024 | 1 | 0 | 1 |
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Below are the most recent publications written about "Supervised Machine Learning" by people in Profiles.
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Shifting to machine supervision: annotation-efficient semi and self-supervised learning for automatic medical image segmentation and classification. Sci Rep. 2024 05 11; 14(1):10820.
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Integrating chromatin conformation information in a self-supervised learning model improves metagenome binning. PeerJ. 2023; 11:e16129.
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Pseudocell Tracer-A method for inferring dynamic trajectories using scRNAseq and its application to B cells undergoing immunoglobulin class switch recombination. PLoS Comput Biol. 2021 05; 17(5):e1008094.
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Label-driven magnetic resonance imaging (MRI)-transrectal ultrasound (TRUS) registration using weakly supervised learning for MRI-guided prostate radiotherapy. Phys Med Biol. 2020 06 26; 65(13):135002.
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Functional Connectivities Are More Informative Than Anatomical Variables in Diagnostic Classification of Autism. Brain Connect. 2019 10; 9(8):604-612.
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A Computable Phenotype for Acute Respiratory Distress Syndrome Using Natural Language Processing and Machine Learning. AMIA Annu Symp Proc. 2018; 2018:157-165.
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RIDDLE: Race and ethnicity Imputation from Disease history with Deep LEarning. PLoS Comput Biol. 2018 04; 14(4):e1006106.
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Supervised machine learning reveals introgressed loci in the genomes of Drosophila simulans and D. sechellia. PLoS Genet. 2018 04; 14(4):e1007341.
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Mapping Patient Trajectories using Longitudinal Extraction and Deep Learning in the MIMIC-III Critical Care Database. Pac Symp Biocomput. 2018; 23:123-132.
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Semi-supervised learning of the electronic health record for phenotype stratification. J Biomed Inform. 2016 12; 64:168-178.