"Cluster Analysis" 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 set of statistical methods used to group variables or observations into strongly inter-related subgroups. In epidemiology, it may be used to analyze a closely grouped series of events or cases of disease or other health-related phenomenon with well-defined distribution patterns in relation to time or place or both.
Descriptor ID |
D016000
|
MeSH Number(s) |
E05.318.740.250 N05.715.360.750.200 N06.850.520.830.250
|
Concept/Terms |
Cluster Analysis- Cluster Analysis
- Analyses, Cluster
- Analysis, Cluster
- Cluster Analyses
- Clustering
- Clusterings
Disease Clustering- Disease Clustering
- Clustering, Disease
- Clusterings, Disease
- Disease Clusterings
|
Below are MeSH descriptors whose meaning is more general than "Cluster Analysis".
Below are MeSH descriptors whose meaning is more specific than "Cluster Analysis".
This graph shows the total number of publications written about "Cluster Analysis" by people in this website by year, and whether "Cluster Analysis" was a major or minor topic of these publications.
To see the data from this visualization as text,
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Year | Major Topic | Minor Topic | Total |
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1995 | 1 | 2 | 3 |
1996 | 1 | 0 | 1 |
1997 | 0 | 1 | 1 |
1999 | 0 | 7 | 7 |
2000 | 1 | 3 | 4 |
2001 | 1 | 6 | 7 |
2002 | 0 | 10 | 10 |
2003 | 0 | 9 | 9 |
2004 | 0 | 18 | 18 |
2005 | 1 | 19 | 20 |
2006 | 0 | 21 | 21 |
2007 | 4 | 35 | 39 |
2008 | 0 | 20 | 20 |
2009 | 0 | 25 | 25 |
2010 | 0 | 41 | 41 |
2011 | 0 | 34 | 34 |
2012 | 0 | 36 | 36 |
2013 | 0 | 46 | 46 |
2014 | 0 | 44 | 44 |
2015 | 1 | 31 | 32 |
2016 | 1 | 25 | 26 |
2017 | 2 | 29 | 31 |
2018 | 1 | 15 | 16 |
2019 | 0 | 14 | 14 |
2020 | 0 | 9 | 9 |
2021 | 0 | 11 | 11 |
2022 | 0 | 12 | 12 |
2023 | 0 | 4 | 4 |
2024 | 0 | 8 | 8 |
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Below are the most recent publications written about "Cluster Analysis" by people in Profiles.
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Clustering computer mouse tracking data with informed hierarchical shrinkage partition priors. Biometrics. 2024 Oct 03; 80(4).
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METI: deep profiling of tumor ecosystems by integrating cell morphology and spatial transcriptomics. Nat Commun. 2024 Aug 25; 15(1):7312.
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Identification of type 1 diabetes risk phenotypes using an outcome-guided clustering analysis. Diabetologia. 2024 Nov; 67(11):2507-2517.
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Multivariate functional principal component analysis and k-means clustering to identify kinematic foot types during gait in children with cerebral palsy. Gait Posture. 2024 Sep; 113:40-45.
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Identification of sleep phenotypes in COPD using machine learning-based cluster analysis. Respir Med. 2024 06; 227:107641.
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Exploring latent clusters in pediatric OCD based on symptoms, severity, age, gender, and comorbidity. Eur Child Adolesc Psychiatry. 2024 Nov; 33(11):3899-3912.
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Cluster-Based Toxicity Estimation of Osteoradionecrosis Via Unsupervised Machine Learning: Moving Beyond Single Dose-Parameter Normal Tissue Complication Probability by Using Whole Dose-Volume Histograms for Cohort Risk Stratification. Int J Radiat Oncol Biol Phys. 2024 Aug 01; 119(5):1569-1578.
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A statistical learning method for simultaneous copy number estimation and subclone clustering with single-cell sequencing data. Genome Res. 2024 02 07; 34(1):85-93.
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SPA-STOCSY: an automated tool for identifying annotated and non-annotated metabolites in high-throughput NMR spectra. Bioinformatics. 2023 10 03; 39(10).
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A Study of Dietary Patterns Derived by Cluster Analysis and Their Association With Metabolic Dysfunction-Associated Steatotic Liver Disease Severity Among Hispanic Patients. Am J Gastroenterol. 2024 03 01; 119(3):505-511.