Publication:
Clustering of European Countries in terms of Healthcare Indicators

cris.virtual.department#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtual.department#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtual.orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtual.orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtualsource.departmentee09e82a-0274-4dd2-8a31-869eb4f8c242
cris.virtualsource.department176e8965-e380-4fc3-a558-46d3417e816d
cris.virtualsource.orcidee09e82a-0274-4dd2-8a31-869eb4f8c242
cris.virtualsource.orcid176e8965-e380-4fc3-a558-46d3417e816d
dc.contributor.authorBillur ECER
dc.contributor.authorAhmet AKTAŞ
dc.contributor.authorAktaş, Ahmet
dc.date.accessioned2024-07-10T14:00:37Z
dc.date.available2024-07-10T14:00:37Z
dc.date.issued2019-03-31
dc.description.abstract<jats:p xml:lang="en">Health is always considered as one of the most important issues related to human being. Due to this importance, governments should primarily provide the best healthcare services to their citizens. Some indicators can show the quality of healthcare services in the country. However, one country can have a higher value of one indicator and can have a lower value of another. Thus, countries can be categorized in terms of quality of healthcare services. Clustering is a useful tool for comparing countries and defining the similar countries in terms of healthcare services. In this study, 28 European Union (EU) countries were evaluated on 14 health factors and the number of clusters was determined by the generally accepted rule of thumb. To cluster countries, k-means clustering method is run in WEKA software for two cluster numbers and four different initial solution approaches. The resulting clusters were evaluated according to the Spearman rank correlation coefficient using the order of the GDP per capita values of the countries in each cluster. It seems using four clusters with Canopy initial solution approach is the most appropriate way of clustering.</jats:p>
dc.identifier.doi10.22399/ijcesen.416611
dc.identifier.urihttps://acikarsiv.thk.edu.tr/handle/123456789/1858
dc.publisherInternational Journal of Computational and Experimental Science and Engineering (IJCESEN)
dc.relation.ispartofInternational Journal of Computational and Experimental Science and Engineering
dc.relation.issn2149-9144
dc.titleClustering of European Countries in terms of Healthcare Indicators
dc.typejournal-article
dspace.entity.typePublication
oaire.citation.issue1
oaire.citation.volume5
relation.isAuthorOfPublication24220193-8eb0-4e42-913b-3161d52c4f56
relation.isAuthorOfPublication.latestForDiscovery24220193-8eb0-4e42-913b-3161d52c4f56

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