Unsupervised Machine Learning
"Unsupervised 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 unlabeled paired input-output training (sample) data.
Descriptor ID |
D000069558
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MeSH Number(s) |
G17.035.250.500.750 L01.224.050.375.530.750
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Concept/Terms |
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Below are MeSH descriptors whose meaning is more general than "Unsupervised Machine Learning".
Below are MeSH descriptors whose meaning is more specific than "Unsupervised Machine Learning".
This graph shows the total number of publications written about "Unsupervised Machine Learning" by people in this website by year, and whether "Unsupervised Machine Learning" 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 |
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2015 | 0 | 1 | 1 | 2018 | 1 | 1 | 2 | 2019 | 0 | 1 | 1 | 2020 | 1 | 0 | 1 | 2021 | 1 | 0 | 1 | 2022 | 0 | 2 | 2 | 2024 | 1 | 3 | 4 |
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Below are the most recent publications written about "Unsupervised Machine Learning" by people in Profiles.
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Rogerson C, Nelson Sanchez-Pinto L, Gaston B, Wiehe S, Schleyer T, Tu W, Mendonca E. Identification of severe acute pediatric asthma phenotypes using unsupervised machine learning. Pediatr Pulmonol. 2024 Dec; 59(12):3313-3321.
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Zhang S, Heil BJ, Mao W, Chikina M, Greene CS, Heller EA. MousiPLIER: A Mouse Pathway-Level Information Extractor Model. eNeuro. 2024 Jun; 11(6).
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Thite NG, Tuberty-Vaughan E, Wilcox P, Wallace N, Calderon CP, Randolph TW. Stain-Free Approach to Determine and Monitor Cell Heath Using Supervised and Unsupervised Image-Based Deep Learning. J Pharm Sci. 2024 Aug; 113(8):2114-2127.
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Greenblott DN, Wood CV, Zhang J, Viza N, Chintala R, Calderon CP, Randolph TW. Supervised and unsupervised machine learning approaches for monitoring subvisible particles within an aluminum-salt adjuvanted vaccine formulation. Biotechnol Bioeng. 2024 May; 121(5):1626-1641.
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Masaracchia L, Fredes F, Woolrich MW, Vidaurre D. Dissecting unsupervised learning through hidden Markov modeling in electrophysiological data. J Neurophysiol. 2023 08 01; 130(2):364-379.
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Angelini ED, Yang J, Balte PP, Hoffman EA, Manichaikul AW, Sun Y, Shen W, Austin JHM, Allen NB, Bleecker ER, Bowler R, Cho MH, Cooper CS, Couper D, Dransfield MT, Garcia CK, Han MK, Hansel NN, Hughes E, Jacobs DR, Kasela S, Kaufman JD, Kim JS, Lappalainen T, Lima J, Malinsky D, Martinez FJ, Oelsner EC, Ortega VE, Paine R, Post W, Pottinger TD, Prince MR, Rich SS, Silverman EK, Smith BM, Swift AJ, Watson KE, Woodruff PG, Laine AF, Barr RG. Pulmonary emphysema subtypes defined by unsupervised machine learning on CT scans. Thorax. 2023 11; 78(11):1067-1079.
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Haldar D, Kazerooni AF, Arif S, Familiar A, Madhogarhia R, Khalili N, Bagheri S, Anderson H, Shaikh IS, Mahtabfar A, Kim MC, Tu W, Ware J, Vossough A, Davatzikos C, Storm PB, Resnick A, Nabavizadeh A. Unsupervised machine learning using K-means identifies radiomic subgroups of pediatric low-grade gliomas that correlate with key molecular markers. Neoplasia. 2023 Feb; 36:100869.
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Yuan NF, Hasenstab K, Retson T, Conrad DJ, Lynch DA, Hsiao A. Unsupervised Learning Identifies Computed Tomographic Measurements as Primary Drivers of Progression, Exacerbation, and Mortality in Chronic Obstructive Pulmonary Disease. Ann Am Thorac Soc. 2022 12; 19(12):1993-2002.
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Barone SM, Paul AG, Muehling LM, Lannigan JA, Kwok WW, Turner RB, Woodfolk JA, Irish JM. Unsupervised machine learning reveals key immune cell subsets in COVID-19, rhinovirus infection, and cancer therapy. Elife. 2021 08 05; 10.
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Leelatian N, Sinnaeve J, Mistry AM, Barone SM, Brockman AA, Diggins KE, Greenplate AR, Weaver KD, Thompson RC, Chambless LB, Mobley BC, Ihrie RA, Irish JM. Unsupervised machine learning reveals risk stratifying glioblastoma tumor cells. Elife. 2020 06 23; 9.
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