dc.contributor.author | Sariyer Ataman, G. | |
dc.contributor.author | Ocal Tasar, C. | |
dc.contributor.author | Cepe, G.E. | |
dc.date.accessioned | 2021-01-25T20:48:25Z | |
dc.date.available | 2021-01-25T20:48:25Z | |
dc.date.issued | 2019 | |
dc.identifier | 10.1515/bams-2018-0044 | |
dc.identifier.issn | 18959091 | |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063092018&doi=10.1515%2fbams-2018-0044&partnerID=40&md5=fdb88a58c0512579ce22b09b5d99dfc0 | |
dc.identifier.uri | https://dspace.yasar.edu.tr/xmlui/handle/20.500.12742/9907 | |
dc.description.abstract | Emergency departments (EDs) are the largest departments of hospitals which encounter high variety of cases as well as high level of patient volumes. Thus, an efficient classification of those patients at the time of their registration is very important fo | |
dc.language.iso | English | |
dc.publisher | Bio-Algorithms and Med-Systems | |
dc.title | Use of data mining techniques to classify length of stay of emergency department patients | |
dc.type | Article | |
dc.relation.volume | 15 | |
dc.relation.issue | 1 | |
dc.description.affiliations | Department of Business Administration, Yaşar University, Izmir, Turkey; Yasar University, Software Engineering, Agaclikli Yol No:35-37, Izmir, Turkey; Baklrçay University, Izmir, Turkey | |