• Typical cluster models include: Connectivity models: for example, hierarchical clustering builds models based on distance connectivity. (wikipedia.org)
  • Hierarchical clustering, bottom-up. (lu.se)
  • Hierarchical clustering is now supported through MeV ( ​ http://www.tm4.org ). (lu.se)
  • The main objective was to get Hierarchical clustering working. (lu.se)
  • k-means clustering and hierarchical clustering . (udemy.com)
  • We present and analyze a new algorithm idea to hierarchically cluster data, and show that it performs well compared to other established hierarchical clustering methods when evaluated based on Dasgupta's cost function. (fu-berlin.de)
  • We prove that in one iteration, our algorithm finds the optimal hierarchical clustering tree for the given order of the points, when limited to hierarchical clustering trees the leaves of which have the same ordering as said points. (fu-berlin.de)
  • Thus, the presented algorithm can be used for hierarchical clustering tasks, or on the results of other hierarchical clustering algorithms to improve those, and leaves room for theoretical improvements and experimentation. (fu-berlin.de)
  • can be used for divisive hierarchical clustering. (howtolearnalanguage.info)
  • Package dynamicTreeCut contains methods for detection of clusters in hierarchical clustering dendrograms. (howtolearnalanguage.info)
  • Package genieclust implements a fast hierarchical clustering algorithm with a linkage criterion which is a variant of the single linkage method combining it with the Gini inequality measure to robustify the linkage method while retaining computational efficiency to allow for the use of larger data sets. (howtolearnalanguage.info)
  • Package hclust1d provides univariate agglomerative hierarchical clustering for a comprehensive choice of linkage functions based on an O ( n log ( n )) algorithm implemented in C++. (howtolearnalanguage.info)
  • Package idendr0 allows to interactively explore hierarchical clustering dendrograms and the clustered data. (howtolearnalanguage.info)
  • Package mdendro provides an alternative implementation of agglomerative hierarchical clustering. (howtolearnalanguage.info)
  • Package protoclust implements a form of hierarchical clustering that associates a prototypical element with each interior node of the dendrogram. (howtolearnalanguage.info)
  • We hypothesized the existence of distinct phenotype-based groups within the very heterogeneous population of patients of heart failure with preserved ejection fraction (HFpEF) and using an unsupervised hierarchical clustering applied to plasma concentration of various biomarkers. (karger.com)
  • Hierarchical clustering is based on the concept of creating a hierarchy of clusters. (resonio.com)
  • Hierarchical clustering can be applied to group similar documents based on their content. (resonio.com)
  • Mass spectra are matched against each other by utilizing extracted peak mass lists and hierarchical clustering. (lu.se)
  • Cluster analysis itself is not one specific algorithm, but the general task to be solved. (wikipedia.org)
  • The appropriate clustering algorithm and parameter settings (including parameters such as the distance function to use, a density threshold or the number of expected clusters) depend on the individual data set and intended use of the results. (wikipedia.org)
  • Centroid models: for example, the k-means algorithm represents each cluster by a single mean vector. (wikipedia.org)
  • Distribution models: clusters are modeled using statistical distributions, such as multivariate normal distributions used by the expectation-maximization algorithm. (wikipedia.org)
  • Relaxations of the complete connectivity requirement (a fraction of the edges can be missing) are known as quasi-cliques, as in the HCS clustering algorithm. (wikipedia.org)
  • with the title "Enhanced path-based Clustering Algorithm" shows the results that path analysis with cluster integration gives results that outperform other cluster algorithms. (frontiersin.org)
  • An in-depth analysis can reveal important insights about the performance of the algorithm, the expected quality of the output clusters, and the possibilities for extracting more relevant information out of a particular data set. (ugent.be)
  • We have extended an existing algorithm for model based clustering of genes to simultaneously cluster genes and conditions, and used 3 large compendia of gene expression data for S. Cerevisiae to analyze its properties. (ugent.be)
  • The algorithm uses a Bayesian approach and a Gibbs sampling procedure to iteratively update the cluster assignment of each gene and condition. (ugent.be)
  • hierarchical agglomerative clustering algorithm was performed using Ward's minimum variance method. (uni-koeln.de)
  • DBSCAN is a density-based clustering algorithm that groups together data points in areas of high density while identifying and separating noise. (resonio.com)
  • Fuzzy C-means , a variation of the K-means algorithm, assigns data points to clusters with varying degrees of membership. (resonio.com)
  • It can be achieved by various algorithms that differ significantly in their understanding of what constitutes a cluster and how to efficiently find them. (wikipedia.org)
  • The notion of a "cluster" cannot be precisely defined, which is one of the reasons why there are so many clustering algorithms. (wikipedia.org)
  • However, different researchers employ different cluster models, and for each of these cluster models again different algorithms can be given. (wikipedia.org)
  • The notion of a cluster, as found by different algorithms, varies significantly in its properties. (wikipedia.org)
  • Understanding these "cluster models" is key to understanding the differences between the various algorithms. (wikipedia.org)
  • This category contains algorithms used for cluster analysis . (wikipedia.org)
  • Aside from their utilit in processing large gap-filled multi-alignments, these algorithms can be applied to a broad spectrum of rRNA analysis functions such as subalignment, phylogenetic subtree extraction and construction, and organism tree-placement, and can serve as a framework to organize sequence data in an efficient and easily searchable manner. (aaai.org)
  • Over the last decade, a large variety of clustering algorithms have been developed to detect coregulatory relationships among genes from microarray gene expression data. (ugent.be)
  • Model based clustering approaches have emerged as statistically well grounded methods, but the properties of these algorithms when applied to large-scale data sets are not always well understood. (ugent.be)
  • Trained on a variety of simulated clustered data, the neural network can classify millions of points from a typical single-molecule localization microscopy data set, with the potential to include additional classifiers to describe different subtypes of clusters. (nature.com)
  • Metal-poor globular clusters in the bulge are important tracers of early chemical evolution. (aanda.org)
  • The information on Galactic assembly time is imprinted on the chemodynamics of globular clusters. (lu.se)
  • The abundance pattern of the globular cluster is compatible with bulge field RR Lyrae stars and in-situ well-studied globular clusters. (lu.se)
  • Its relatively low metallicity with respect to old and moderately metal-poor inner Galaxy clusters may suggest a low-metallicity floor for globular clusters that formed in-situ in the early Galactic bulge. (lu.se)
  • Find clusters of DNA sequences based on their global similarity to two reference sequences. (wolfram.com)
  • A major issue in the analysis of clustered data is that observations within a cluster are not independent, and the degree of similarity is typically measured by the intracluster correlation coefficient (ICC). (annfammed.org)
  • Agglomerative clustering starts with individual data points as clusters and merges them iteratively based on similarity, whereas divisive clustering begins with one cluster containing all data points and splits it successively. (resonio.com)
  • Additionally, it may specify the relationship of the clusters to each other, for example, a hierarchy of clusters embedded in each other. (wikipedia.org)
  • from package stats and associated methods can be used for improved visualization for cluster dendrograms. (howtolearnalanguage.info)
  • The output is presented as dendrograms in which protein isoforms cluster together. (lu.se)
  • A collection of distinct equivalent clusterings can be summarized as a weighted graph on the set of genes, from which we extract fuzzy, overlapping clusters using a graph spectral method. (ugent.be)
  • The cores of these fuzzy clusters contain tight sets of strongly coexpressed genes, while the overlaps exhibit relations between genes showing only partial coexpression. (ugent.be)
  • Fuzzy C-means clustering can be used for image segmentation, where the goal is to divide an image into regions that share similar characteristics. (resonio.com)
  • When the clusters are relatively homogeneous (that is, the intra-cluster correlation is small), parallel studies tend to deliver better statistical performance than a stepped wedge trial. (bmj.com)
  • According to Solimun [ 4 ], cluster analysis is used to group homogeneous objects into one and the characteristics between groups are heterogeneous. (frontiersin.org)
  • ABSTRACT To determine the distribution and correlates of clustering of cardiovascular disease (CVD) risk factors, data from the Oman National Health Survey, 2000 were analysed. (who.int)
  • There are different approaches to analyzing molecular data to identify clusters, and not all focus on identifying rapid transmission. (cdc.gov)
  • Also, clustering with absolute correlation as the distance metric does not work very well at all. (lu.se)
  • 1 Ignoring the intracluster correlation in the analysis could lead to incorrect P values, confidence intervals that are too small, and biased estimates and effect sizes, all of which can lead to incorrect interpretation of associations between variables. (annfammed.org)
  • In most situations, the numeric value of the intra-cluster correlation tends to be small and positive. (annfammed.org)
  • Investigators need to be aware that the cluster effect is a combination of both the intracluster correlation and the cluster size. (annfammed.org)
  • Examples in the Killip et al article show how the intracluster correlation, number of observations within a cluster, and number of clusters are all interrelated in estimating sample size and power for clustered data. (annfammed.org)
  • 8 Hence, multilevel analyses are designed to analyze variables from different levels simultaneously, all the while taking into account the intracluster correlation. (annfammed.org)
  • Besides the term clustering, there is a number of terms with similar meanings, including automatic classification, numerical taxonomy, botryology (from Greek βότρυς "grape"), typological analysis, and community detection. (wikipedia.org)
  • HIV cluster detection identifies communities affected by rapid HIV transmission . (cdc.gov)
  • Analyses should include time-space and molecular cluster detection. (cdc.gov)
  • CDC has provided Secure HIV-TRACE, a secure, web-based application for health departments to use for molecular cluster detection. (cdc.gov)
  • Numerous related issues--such as the epidemiologic workup of infectious disease outbreaks, the assessment of the health effects of environmental exposures, the prospective detection of clusters, and the investigation of interpersonal networks--are not addressed. (cdc.gov)
  • Four clusters emerged with statistically different systolic and diastolic blood pressure and heart rate reactivity patterns. (stir.ac.uk)
  • This takes little RAM, allowing you to cluster a large number of genes, but the clustering results could be inferior to those obtained with e.g. average linkage. (lu.se)
  • This study aims to compare integrated clusters on various linkages (Ward, Complete, and Average linkage) with path analysis to classify the behavior of subservient to pay for mortgages. (frontiersin.org)
  • So, this study uses the cluster integration with path analysis method by comparing the linkage. (frontiersin.org)
  • The results showed that cluster integration in the Ward linkage method with path analysis was the best method, by comparing the coefficient of determination. (frontiersin.org)
  • This study examines the application of integrated clusters in path analysis with three different linkage methods, namely Ward linkage, Complete linkage, and Average linkage. (frontiersin.org)
  • In this study, we want to examine the effect of using linkage on the integrated Cluster path analysis approach. (frontiersin.org)
  • From this research, we want to get the best linkage to be used in the integrated Cluster path analysis approach to classify the behavior of compliant to pay for the type of KPR Purchase. (frontiersin.org)
  • 9- , 11 While the two articles featured in this issue help raise awareness of the challenges and some solutions to analyzing clustered data, the skills required for optimal analysis of clustered data often are beyond those of most clinician-investigators. (annfammed.org)
  • Package ClusterR implements k-means, mini-batch-kmeans, k-medoids, affinity propagation clustering and Gaussian mixture models with the option to plot, validate, predict (new data) and estimate the optimal number of clusters. (howtolearnalanguage.info)
  • It is a main task of exploratory data analysis, and a common technique for statistical data analysis, used in many fields, including pattern recognition, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine learning. (wikipedia.org)
  • Popular notions of clusters include groups with small distances between cluster members, dense areas of the data space, intervals or particular statistical distributions. (wikipedia.org)
  • Density models: for example, DBSCAN and OPTICS defines clusters as connected dense regions in the data space. (wikipedia.org)
  • A "clustering" is essentially a set of such clusters, usually containing all objects in the data set. (wikipedia.org)
  • Quantifying the extent to which points are clustered in single-molecule localization microscopy data is vital to understanding the spatial relationships between molecules in the underlying sample. (nature.com)
  • Many existing computational approaches are limited in their ability to process large-scale data sets, to deal effectively with sample heterogeneity, or require subjective user-defined analysis parameters. (nature.com)
  • This list can be plotted and rasterized for examination with conventional image analysis tools, but an ideal method would operate on the original coordinate data without requiring its transformation. (nature.com)
  • Common among many of these approaches is the selection of analysis parameters, which can lead to a suboptimal interpretation of the data, for example, when points are clustered at a different spatial scale to the one used for assessment or when points are not homogeneously clustered. (nature.com)
  • Data collection continues throughout the study, so that each cluster contributes observations under both control and intervention observation periods. (bmj.com)
  • Cluster analysis is a staple of unsupervised machine learning and data science . (udemy.com)
  • We identified several SM-encoding biosynthetic gene clusters (BGCs) from the metagenomic data of lean and obese individuals and found significant association between some BGCs, including those that produce hitherto unknown SM, and obesity. (hindawi.com)
  • These studies generate data that are clustered. (annfammed.org)
  • A special case of clustered data is an intervention study where clinicians or practices are randomized into an intervention or control group. (annfammed.org)
  • Although clustered data are common, investigators often overlook both the special analysis challenges and the unique opportunities inherent with clustered data. (annfammed.org)
  • 4, 5 In this issue of the Annals , Reed suggests a convenient correction procedure to address clustered data. (annfammed.org)
  • Also in this issue, the article by Killip et al 7 provides a formula to compute an effective sample size for clustered data. (annfammed.org)
  • Clustered data imply a hierarchical nature to the data, and while many levels can be considered, two levels are most commonly specified. (annfammed.org)
  • Considering an example of data with patients clustered with physicians, a comprehensive multilevel data analysis aims to assess the direct effect of patient and clinician/practice level variables on the outcome. (annfammed.org)
  • Statistical software to conduct these types of analyses and for computing sample size for clustered data now exist, and we encourage their wider use. (annfammed.org)
  • Studies involving clustered data would greatly benefit from the expertise provided by statisticians versed in the analysis of clustered data. (annfammed.org)
  • For large-scale data sets, the posterior distribution is strongly peaked on a limited number of equiprobable clusterings. (ugent.be)
  • Joshi, A. , Van de Peer, Y. , Michoel, T. (2008) Analysis of a Gibbs sampler method for model based clustering of gene expression data. (ugent.be)
  • Health departments can identify HIV clusters through analyzing surveillance data. (cdc.gov)
  • Health departments should analyze HIV surveillance data monthly to quickly identify and monitor HIV clusters. (cdc.gov)
  • Analyses of HIV sequence data reported to HIV surveillance programs shouldn't be interpreted as determining transmission direction or showing direct transmission between individuals. (cdc.gov)
  • DESIGN: Food frequency data were converted to percentage of total energy from 38 food groups and entered into a cluster analysis procedure. (lu.se)
  • By the end of this guide, you will have a thorough understanding of cluster analysis and its benefits, enabling you to make informed decisions when it comes to analyzing your own data. (resonio.com)
  • It is an exploratory analysis that identifies structures within data sets and tries to identify homogenous groups of cases. (resonio.com)
  • Cluster analysis can handle binary, nominal, ordinal, and scale data, and it is often used in conjunction with other analyses such as discriminant analysis. (resonio.com)
  • Cluster analysis has many real-world applications, such as in unsupervised machine learning, data mining, statistics, Graph Analytics, image processing, and numerous physical and social science applications. (resonio.com)
  • This method allows for overlapping clusters, enabling a more nuanced understanding of data relationships. (resonio.com)
  • I am working on a clustering analysis of time series data in R using the dtwclust package, specifically the tsclust function. (stackoverflow.com)
  • I am attempting to construct a 'big data' approach for time series classification using dynamic time warping (DTW) and knn clustering. (stackoverflow.com)
  • One interesting fact is that under certain conditions, Gaussian mixture models and k-means clustering are exactly the same! (udemy.com)
  • We recently reported the usefulness of applying mathematical models ( i.e. principal component and cluster analyses) to multiple variables for the identification of clinical phenotypes in a cohort of COPD subjects [ 4 ]. (ersjournals.com)
  • These original analyses allowed the description of four COPD groups, which we called "clinical COPD phenotypes" [ 4 ]. (ersjournals.com)
  • These authors suggested that, before being referred to as clinical phenotypes, clusters of related patients require longitudinal validation to determine how they differ with respect to important clinical outcomes [ 2 ]. (ersjournals.com)
  • This cluster analysis identified tinct phenotypes, which differed in clinical presentation, response to therapy, and survival. (uni-koeln.de)
  • According to the obtained heat map of this analysis, we concluded two distinctive biomarker phenotypes within the HFpEF. (karger.com)
  • parameter is included in the request the servlet will only return clusters that has that configuration option. (lu.se)
  • We present an analysis of multi-aligned eukaryotic and procaryotic small subunit rRNA sequences using a novel segmentation and clustering procedure capable of extracting subsets of sequences that share common sequence features. (aaai.org)
  • STATISTICAL ANALYSIS PERFORMED: Subjects were clustered according to food energy sources using the FASTCLUS procedure in the Statistical Analysis System. (lu.se)
  • Low morbidity jurisdictions (areas that have low numbers of HIV diagnoses) may conduct analyses as needed when new diagnoses or molecular sequences are reported. (cdc.gov)
  • The weaker "clusterability axiom" (no cycle has exactly one negative edge) yields results with more than two clusters, or subgraphs with only positive edges. (wikipedia.org)
  • All Project participants fall in the expected clusters, so there is no need to report any individual clustering results. (blogspot.com)
  • The results of determining many clusters with different linkages will certainly give different results. (frontiersin.org)
  • RESULTS: Six food pattern clusters were identified. (lu.se)
  • Introduction: The results of a 2001-2005 polycythemia vera (PV) investigation in Eastern Pennsylvania revealed a disease cluster plus underreporting and false reporting to the Pennsylvania Cancer Registry (PCR). (cdc.gov)
  • DBSCAN is particularly useful for datasets with noise or when clusters have varying densities. (resonio.com)
  • However, if substantial cluster-level effects are present (that is, larger intra-cluster correlations) or the clusters are large, the stepped wedge design will be more powerful than a parallel design, even one in which the intervention is preceded by a period of baseline control observations. (bmj.com)
  • Small intracluster correlations coupled with large cluster size can still affect the validity of conventional statistical analyses. (annfammed.org)
  • In investor trading, cluster analysis is used to develop a diversified portfolio by grouping stocks that exhibit high correlations in returns into one basket, those slightly less correlated in another, and so on. (resonio.com)
  • Graph-based models: a clique, that is, a subset of nodes in a graph such that every two nodes in the subset are connected by an edge can be considered as a prototypical form of cluster. (wikipedia.org)
  • One-way analysis of variance and chi 2 analysis were then performed to compared the weight status, nutrient intakes, and demographics of the food patterns. (lu.se)
  • CONCLUSIONS: The success of cluster analysis in identifying dietary exposure categories with unique demographic and nutritional correlates suggests that the approach may be useful in epidemiologic studies that examine conditions such as obesity, and in the design of nutrition interventions. (lu.se)
  • 2 Failure to take into account the clustered structure of the study design during the planning phase of the study also can lead to underpowered study designs in which the effective sample size and statistical power to detect differences are smaller than planned. (annfammed.org)
  • Statistical methods that can be used to deal with these problems are using cluster integration and path analysis [ 3 ]. (frontiersin.org)
  • In addition to having epidemiologic and statistical expertise, health agencies should recognize the social dimensions of a cluster and should develop an approach for investigating clusters that best maintains critical community relationships and that does not excessively deplete resources. (cdc.gov)
  • Although a systematic approach is vital, health agencies should be flexible in their method of analysis and tests of statistical significance. (cdc.gov)
  • To provide epidemiologic and statistical source material to state and local health agencies to aid in their development of a systematic approach to the evaluation of clusters of health events. (cdc.gov)
  • In dealing with cluster reports, the general public is not likely to be satisfied with complex epidemiologic or statistical arguments that deny the existence or importance of a cluster. (cdc.gov)
  • As a widely used statistical method, cluster analysis helps to identify groups of similar objects within a dataset, making it a valuable tool in fields such as market research , biology, and psychology. (resonio.com)
  • Cluster analysis is a statistical method used to group items into clusters based on how closely associated they are. (resonio.com)
  • VLT-FLAMES analysis of 8 giants in the bulge metal-poor globular cluster NGC 6522: oldest cluster in the Galaxy? (aanda.org)
  • Given the consistency of the small-r e galaxies' stellar surface densities (and even colors) with those of systems more than ten times as massive, our findings suggest that clusters mark places where galaxy evolution is accelerated for an ancient base population spanning most masses, with late-time additions quenched by environment-specific mechanisms mainly restricted to the lowest masses. (caltech.edu)
  • A GO annotation analysis shows that these local maxima are all biologically equally significant, and that simultaneously clustering genes and conditions performs better than only clustering genes and assuming independent conditions. (ugent.be)
  • Brindle RC, Ginty AT, Jones A, Phillips AC, Roseboom TJ, Carroll D, Painter RC & de Rooij SR (2016) Cardiovascular reactivity patterns and pathways to hypertension: a multivariate cluster analysis. (stir.ac.uk)
  • For this reason multivariate cluster analysis was carried out to examine the relationship between heart rate and blood pressure reactivity patterns and hypertension in a large prospective cohort (age range 55-60 years). (stir.ac.uk)
  • Cluster analysis as such is not an automatic task, but an iterative process of knowledge discovery or interactive multi-objective optimization that involves trial and failure. (wikipedia.org)
  • The design involves random and sequential crossover of clusters from control to intervention until all clusters are exposed. (bmj.com)
  • 6 The correction involves applying a formula to the standard errors and then conducting the planned analysis with the corrected standard errors. (annfammed.org)
  • In such cluster-randomized designs, all patients of a clinician or practice are assigned to the same treatment, and this design is often used when logistics of implementation or the need to avoid contamination of treatment arms is a priority. (annfammed.org)
  • CDC's approach identifies clusters of rapid transmission, and the most concerning of these are known as "national priority clusters. (cdc.gov)
  • Health departments should respond to all national priority clusters. (cdc.gov)
  • Secure HIV-TRACE identifies national priority clusters and other concerning clusters. (cdc.gov)
  • Health departments can also develop their own approaches to time-space analysis. (cdc.gov)
  • it would be third with such characteristics, but it differs from them, since these two other clusters have also a populous Red HB, and a normal slope of the RGB for their metallicity, which is not the case of HP-1. (aanda.org)
  • Definition, Background, and Characteristics of Clusters As used in these guidelines, the term 'cluster' is an unusual aggregation, real or perceived, of health events that are grouped together in time and space and that are reported to a health agency. (cdc.gov)
  • The purpose of cluster analysis is to find similar groups of subjects based on a global measure over the whole set of characteristics. (resonio.com)
  • Patients in Cluster 1 had a better response to PAH treatment than patients in the 2 other clusters. (uni-koeln.de)
  • Clustering analysis of the patients according to their NFHAS resulted in five groups. (bvsalud.org)
  • In addition, euglycaem- been accompanied by cultural changes, a ic patients with hyperinsulinaemia had a reduction in the prevalence of communica- cluster of risk factors for CVD. (who.int)
  • As the clustering values can depend strongly on the overall density and arrangement of points, it is likely that the appropriate threshold for one image will be unsuitable for the next. (nature.com)
  • Time-space increases need further investigation because they may indicate one large cluster, many small clusters, or an increase in HIV testing that has led to new diagnoses of older infections. (cdc.gov)
  • Clustering can therefore be formulated as a multi-objective optimization problem. (wikipedia.org)
  • The objective of our study was to explore the phenomenon of meningococcal clustering in a more objective way by using a nearest-neighbor analysis in space and time that compares the actual occurrence of clusters with their background incidence. (cdc.gov)
  • OBJECTIVE: This study explored the usefulness of cluster analysis in identifying food choice patterns of three groups of adults in relation to their energy intake. (lu.se)
  • Neural models: the most well known unsupervised neural network is the self-organizing map and these models can usually be characterized as similar to one or more of the above models, and including subspace models when neural networks implement a form of Principal Component Analysis or Independent Component Analysis. (wikipedia.org)
  • Subsequently, at regular intervals (the "steps") one cluster (or a group of clusters) is randomised to cross from the control to the intervention under evaluation. (bmj.com)
  • Time-space analysis identifies increases in HIV diagnoses in a particular geographic area or population. (cdc.gov)
  • To investigate the early evolution of the Galactic bulge, we analysed the globular cluster NGC 6355. (lu.se)
  • We derived chemical abundances and kinematic and dynamic properties by gathering information from high-resolution spectroscopy with FLAMES-UVES, photometry with the Hubble Space Telescope, and Galactic dynamic calculations applied to the globular cluster NGC 6355. (lu.se)
  • Additionally, HIV clusters can be identified by providers, partner services and frontline staff, and community members. (cdc.gov)
  • Except for packages stats and cluster (which essentially ship with base R and hence are part of every R installation), each package is listed only once. (howtolearnalanguage.info)
  • For instance, researchers can analyze a large set of news articles and cluster them by topics, such as sports, politics, and entertainment. (resonio.com)
  • Subjects in the two clusters associated with high consumption of pastry and meat had significantly higher fat intakes (P = .0001). (lu.se)
  • Subjects in two other clusters, those associated with high intake of skim milk and a broad distribution of energy sources had significantly higher micronutrient levels (P = .0001). (lu.se)
  • Body mass index and the distribution of gender were also significantly different across clusters. (lu.se)
  • The first 4 of these for age, hypertensive men had significantly may cluster in some persons and have been higher total cholesterol, fasting blood sug- identified as components of a syndrome ar, body mass index (BMI) and waist-hip known as metabolic cardiovascular syn- ratio than their normotensive counterparts. (who.int)
  • Sur la base des données démographiques (tension artérielle, glycémie à jeun, cholestérol sérique, mesures du poids, de la taille, du tour de taille et de hanches), 5660 sujets ont été groupés en fonction du nombre de facteurs de risque de maladie cardio-vasculaire qu'ils avaient parmi les quatre suivants : hypertension, cholestérol élevé, diabète, surcharge pondérale/obésité. (who.int)
  • A distribution of points within the imaging field can be interrogated using spatial point pattern analyses to reveal the spatial relationships between the points and higher-scale relationships between clusters of points, or between points from different imaging channels. (nature.com)
  • More complex analyses-{r} e =f({M} * ,U-V,n,z,{{Σ }})-reveal local density (Σ) to induce only a 7% ± 3% (95% confidence) reduction in r e beyond what can be accounted for by U - V color, Sérsic index (n), and redshift (z) effects. (caltech.edu)
  • Outbreaks are recognized when place (e.g., an educational institution like a primary school), time (e.g., within 1 month), and conventional phenotypic markers (same serogroup, serotype, and subtype) make a connection likely (field cluster) or when an excess of incidence (e.g., 20x normal) is noticed in a retrospectively specified geographic or population area within a chosen period (community outbreak). (cdc.gov)
  • Clinical providers or community members may help identify HIV clusters. (cdc.gov)
  • Health departments conduct molecular analysis using a portion of the genetic sequence of HIV that comes from HIV drug resistance testing. (cdc.gov)
  • Molecular analysis examines the genetic sequence of the virus, not the person. (cdc.gov)
  • Accommodating error analysis in comparison and clustering of molecular fingerprints. (cdc.gov)
  • and iii) intersection of clusters associated with each conserved segment. (aaai.org)
  • In marketing, cluster analysis is used to segment customers into groups based on their purchasing behavior or preferences. (resonio.com)
  • Companies can use K-means clustering to segment their customer base based on various features, such as age, income, and purchase history. (resonio.com)
  • According to Sudaryono [ 6 ] path analysis is a method that examines the direct and indirect effects of the hypothesized variables. (frontiersin.org)
  • K-means clustering is a widely-used, centroid-based partitioning method. (resonio.com)
  • Implemented a method for automatically selecting a different cluster if the current one is not configured for use with a particular analysis step. (lu.se)
  • Improving the staging of neck injuries using a new index, the Neck Functional Holistic Analysis Score: Clustering approach to determine degrees of impairment. (bvsalud.org)
  • Clusters are recognized when meningococcal cases of the same phenotypic strain (markers: serogroup, serotype, and subtype) occur in spatial and temporal proximity. (cdc.gov)
  • A group of unrelated cases that occur in temporal and spatial proximity may be misinterpreted as a cluster or outbreak, but these cases would not justify additional public health measures, except perhaps to reassure the public. (cdc.gov)
  • In a real cluster, cases of the same strain occur in temporal and spatial proximity at a higher frequency than by chance. (cdc.gov)
  • Cluster 3 was characterised by blunted cardiovascular stress reactivity across all variables and cluster 4, by an exaggerated blood pressure response and modest heart rate response. (stir.ac.uk)
  • studied the clustering to the rise in cardiovascular disease (CVD) of CVD risk factors in hypertensive pa- risk factors [ 2 ]. (who.int)
  • The incidence of such clusters was compared to the incidence that would be expected by chance by using space-time nearest-neighbor analysis of 4,887 confirmed invasive meningococcal cases identified in the 9-year surveillance period 1993-2001 in the Netherlands. (cdc.gov)
  • The analyses were conducted to determine sensitivity and positive predictive value (PPV) of case reporting to the PCR, estimate cancer incidence rates, and evaluate the presence of cancer clusters. (cdc.gov)
  • This need to be changed so that a different cluster is selected if the next step is not available on the same cluster. (lu.se)
  • from package cluster implements partitioning around medoids and can work with arbitrary distances. (howtolearnalanguage.info)
  • It does not require a predefined number of clusters, as it can find arbitrary shapes and sizes of clusters based on the data's density distribution. (resonio.com)
  • Sample size calculations and analysis must make allowance for both the clustered nature of the design and the confounding effect of time. (bmj.com)