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 | 0 | 1 |
| 2022 | 0 | 1 | 1 |
| 2023 | 0 | 1 | 1 |
| 2024 | 1 | 1 | 2 |
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Below are the most recent publications written about "Supervised Machine Learning" by people in Profiles.
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Weakly Supervised Classification of Mohs Surgical Sections Using Artificial Intelligence. Mod Pathol. 2025 Feb; 38(2):100653.
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Semi-supervised machine learning method for predicting homogeneous ancestry groups to assess Hardy-Weinberg equilibrium in diverse whole-genome sequencing studies. Am J Hum Genet. 2024 Oct 03; 111(10):2129-2138.
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Active Learning Pipeline to Identify Candidate Terms for a CDSS Ontology. Stud Health Technol Inform. 2024 Aug 22; 316:1338-1342.
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Evolutionary Action-Machine Learning Model Identifies Candidate Genes Associated With Early-Onset Coronary Artery Disease. J Am Heart Assoc. 2023 09 05; 12(17):e029103.
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Computational epitope mapping of class I fusion proteins using low complexity supervised learning methods. PLoS Comput Biol. 2022 12; 18(12):e1010230.
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Fully automated quality control of rigid and affine registrations of T1w and T2w MRI in big data using machine learning. Comput Biol Med. 2021 12; 139:104997.
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Clustering of Largely Right-Censored Oropharyngeal Head and Neck Cancer Patients for Discriminative Groupings to Improve Outcome Prediction. Sci Rep. 2020 03 02; 10(1):3811.
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Learning predictive models of drug side-effect relationships from distributed representations of literature-derived semantic predications. J Am Med Inform Assoc. 2018 10 01; 25(10):1339-1350.
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Computational Principles of Supervised Learning in the Cerebellum. Annu Rev Neurosci. 2018 07 08; 41:233-253.
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Extracting information from the shape and spatial distribution of evoked potentials. J Neurosci Methods. 2018 02 15; 296:12-22.