Clustering of Phentermine HCL Drug from Online Patient Medication Reviews

dc.authorscopusid6505872114
dc.authorscopusid57210928462
dc.contributor.authorYildirim, Pinar
dc.contributor.authorKaya, Alkan
dc.contributor.otherBilgisayar Mühendisliği / Computer Engineering
dc.contributor.otherTıbbi Mikrobiyoloji / Medical Microbiology
dc.date.accessioned2024-05-25T11:40:37Z
dc.date.available2024-05-25T11:40:37Z
dc.date.issued2019
dc.departmentOkan Universityen_US
dc.department-temp[Yildirim, Pinar] Istanbul Okan Univ, Fac Engn, Dept Comp Engn, Istanbul, Turkey; [Kaya, Alkan] Rmg Petrol Urunleri Dagitim AS, Istanbul, Turkeyen_US
dc.description.abstractIn this paper, a study to reveal hidden knowledge in the online patient medication reviews for phentermine HCL is presented. Phentermine HCL is used most frequently in the treatment of obesity. Obesity is a complex health disorder that affects huge amount of people. In recent years, the number of overweight people in industrialized countries has increased significantly and people who are obese are at a much higher risk for serious medical conditions such as high blood pressure, heart attack, stroke and diabetes. Considering the importance of the medication of obesity, knowledge discovery from online patient reviews is performed. Some information technologies and data mining techniques are used to discover some hidden knowledge between patient information and side effects in these reviews. Our results can give new ideas to medical researchers and pharmaceutical industry for drug safety. (C) 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the Conference Program Chairs.en_US
dc.identifier.citationcount0
dc.identifier.doi10.1016/j.procs.2019.04.163
dc.identifier.endpage1151en_US
dc.identifier.issn1877-0509
dc.identifier.scopus2-s2.0-85071911005
dc.identifier.scopusqualityQ2
dc.identifier.startpage1146en_US
dc.identifier.urihttps://doi.org/10.1016/j.procs.2019.04.163
dc.identifier.urihttps://hdl.handle.net/20.500.14517/1452
dc.identifier.volume151en_US
dc.identifier.wosWOS:000577067400158
dc.institutionauthorYıldırım, Pınar
dc.institutionauthorKaya A.
dc.institutionauthorKaya, Ayşe Demet
dc.institutionauthorYıldırım, Pınar
dc.institutionauthorKaya, Ayşe Demet
dc.language.isoen
dc.publisherElsevieren_US
dc.relation.ispartof10th International Conference on Ambient Systems, Networks and Technologies (ANT) / 2nd International Conference on Emerging Data and Industry 4.0 (EDI40) -- APR 29-MAY 02, 2019 -- Leuven, BELGIUMen_US
dc.relation.ispartofseriesProcedia Computer Science
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.scopus.citedbyCount0
dc.subjectBiomedical Data Miningen_US
dc.subjectclusteringen_US
dc.subjectk-means algorithmen_US
dc.subjectdrug side effectsen_US
dc.subjectWebMDen_US
dc.titleClustering of Phentermine HCL Drug from Online Patient Medication Reviewsen_US
dc.typeConference Objecten_US
dc.wos.citedbyCount0
dspace.entity.typePublication
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