{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["101(38)"],"submitter":["Wang CY"],"pubmed_abstract":["<h4>Background</h4>Polycystic kidney disease (PKD) is a genetic disorder in which the renal tubules become structurally abnormal, resulting in the development and growth of multiple cysts within the kidneys. Numerous studies on PKD have been published in the literature. However, no such articles used medical subject headings (MeSH terms) to predict the number of article citations. This study aimed to predict the number of article citations using 100 top-cited PKD articles (T100PKDs) and dissect the characteristics of influential authors and affiliated counties since 2010.<h4>Methods</h4>We searched the PubMed Central® (PMC) database and downloaded 100PKDs from 2010. Citation analysis was performed to compare the dominant countries and authors using social network analysis (SNA). MeSh terms"],"journal":["Medicine"],"pagination":["e30632"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9509201"],"repository":["biostudies-literature"],"pubmed_title":["Predicting the number of citations of polycystic kidney disease with 100 top-cited articles since 2010: Bibliometric analysis."],"pmcid":["PMC9509201"],"pubmed_authors":["Chou W","Wang CY","Chien TW","Wang HY"],"additional_accession":[]},"is_claimable":false,"name":"Predicting the number of citations of polycystic kidney disease with 100 top-cited articles since 2010: Bibliometric analysis.","description":"<h4>Background</h4>Polycystic kidney disease (PKD) is a genetic disorder in which the renal tubules become structurally abnormal, resulting in the development and growth of multiple cysts within the kidneys. Numerous studies on PKD have been published in the literature. However, no such articles used medical subject headings (MeSH terms) to predict the number of article citations. This study aimed to predict the number of article citations using 100 top-cited PKD articles (T100PKDs) and dissect the characteristics of influential authors and affiliated counties since 2010.<h4>Methods</h4>We searched the PubMed Central® (PMC) database and downloaded 100PKDs from 2010. Citation analysis was performed to compare the dominant countries and authors using social network analysis (SNA). MeSh terms","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Sep","modification":"2025-04-04T09:24:55.276Z","creation":"2025-04-04T09:24:55.276Z"},"accession":"S-EPMC9509201","cross_references":{"pubmed":["36197211"],"doi":["10.1097/MD.0000000000030632"]}}