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The Importance of Multidisciplinary in Data Science: Application of the Method in Health Sector to Telecommunication Sector

dc.contributor.authorKurt, Kenan Kaan
dc.contributor.authorAtay, Huseyin Tanzer
dc.contributor.authorCicek, Mustafa Alpkan
dc.contributor.authorKaraca, Saffet Baris
dc.contributor.authorTurkeli, Serkan
dc.date.accessioned2026-01-24T13:15:55Z
dc.date.issued2019-09-01
dc.description.abstractThe aim of this article is to reveal the importance of multi-disciplinary perspective in data science. For this aim, the authors applied the survival analysis method developed in the health sector to the telecommunication sector data. As a result of the inadequacy of traditional data science methods on the data obtained, the authors have searched for different methods and the authors who have a master's degree in biomedical studies were found similarity between churn and survival. With this paper, we try to prove the benefit of being multi-disciplinary who want to study data science.
dc.description.urihttps://doi.org/10.1109/idap.2019.8875917
dc.description.urihttps://dx.doi.org/10.1109/idap.2019.8875917
dc.identifier.doi10.1109/idap.2019.8875917
dc.identifier.endpage4
dc.identifier.openairedoi_dedup___::009d2952b4ec95b766bb67d01ed6e8e5
dc.identifier.orcid0000-0002-0708-1945
dc.identifier.startpage1
dc.identifier.urihttps://hdl.handle.net/11527/32732
dc.publisherIEEE
dc.relation.ispartof2019 International Artificial Intelligence and Data Processing Symposium (IDAP)
dc.rightsCLOSED
dc.titleThe Importance of Multidisciplinary in Data Science: Application of the Method in Health Sector to Telecommunication Sector
dc.typeArticle
dspace.entity.typePublication

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