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Prediction Of Similarities Among Rheumatic Diseases

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dc.contributor.author Yıldırım, Pınar
dc.contributor.author Çeken, Çınar
dc.contributor.author Hassanpour, Reza
dc.contributor.author Tolun, Mehmet R.
dc.date.accessioned 2020-04-07T17:26:09Z
dc.date.available 2020-04-07T17:26:09Z
dc.date.issued 2012-06
dc.identifier.citation Yildirim, Pinar...et al. "Prediction of Similarities Among Rheumatic Diseases", Journal Of Medıcal Systems, Vol. 36, No. 3, pp. 1485-1490, (2012) tr_TR
dc.identifier.issn 0148-5598
dc.identifier.issn 1573-689X
dc.identifier.uri http://hdl.handle.net/20.500.12416/2956
dc.description.abstract We introduce a method for extracting hidden patterns seen in rheumatic diseases by using articles from the widely used biomedical database MEDLINE. Rheumatic diseases affect hundreds of millions of people worldwide and lead to substantial loss of functioning and mobility. Diagnosing rheumatic diseases can be difficult because some symptoms are common to many of them. We use Facta system as a biomedical text mining tool for finding symptoms and then create a dataset with the frequencies of symptoms for each disease and apply hierarchical clustering analysis to find similarities between diseases. Clustering analysis yields four distinct types or groups of rheumatic diseases. Although our results cannot remove all the uncertainty for the diagnosis of rheumatic diseases, we believe they can contribute to the diagnosis of rheumatic diseases to a certain extent. We hope that some similarities exposed can provide additional information at the stage of decision-making. tr_TR
dc.language.iso eng tr_TR
dc.publisher Springer tr_TR
dc.relation.isversionof 10.1007/s10916-010-9609-6 tr_TR
dc.rights info:eu-repo/semantics/closedAccess tr_TR
dc.subject Biomedical Text Mining tr_TR
dc.subject Rheumatic Diseases tr_TR
dc.subject Hierarchical Cluster Analysis tr_TR
dc.subject Information Extraction tr_TR
dc.title Prediction Of Similarities Among Rheumatic Diseases tr_TR
dc.type article tr_TR
dc.relation.journal Journal Of Medıcal Systems tr_TR
dc.contributor.authorID 101956 tr_TR
dc.identifier.volume 36 tr_TR
dc.identifier.issue 3 tr_TR
dc.identifier.startpage 1485 tr_TR
dc.identifier.endpage 1490 tr_TR
dc.contributor.department Çankaya Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü tr_TR


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