Clustering of Phentermine HCL Drug from Online Patient Medication Reviews
dc.authorscopusid | 6505872114 | |
dc.authorscopusid | 57210928462 | |
dc.contributor.author | Yildirim, Pinar | |
dc.contributor.author | Kaya, Alkan | |
dc.contributor.other | Bilgisayar Mühendisliği / Computer Engineering | |
dc.contributor.other | Tıbbi Mikrobiyoloji / Medical Microbiology | |
dc.date.accessioned | 2024-05-25T11:40:37Z | |
dc.date.available | 2024-05-25T11:40:37Z | |
dc.date.issued | 2019 | |
dc.department | Okan University | en_US |
dc.department-temp | [Yildirim, Pinar] Istanbul Okan Univ, Fac Engn, Dept Comp Engn, Istanbul, Turkey; [Kaya, Alkan] Rmg Petrol Urunleri Dagitim AS, Istanbul, Turkey | en_US |
dc.description.abstract | In 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.citationcount | 0 | |
dc.identifier.doi | 10.1016/j.procs.2019.04.163 | |
dc.identifier.endpage | 1151 | en_US |
dc.identifier.issn | 1877-0509 | |
dc.identifier.scopus | 2-s2.0-85071911005 | |
dc.identifier.scopusquality | Q2 | |
dc.identifier.startpage | 1146 | en_US |
dc.identifier.uri | https://doi.org/10.1016/j.procs.2019.04.163 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14517/1452 | |
dc.identifier.volume | 151 | en_US |
dc.identifier.wos | WOS:000577067400158 | |
dc.institutionauthor | Yıldırım, Pınar | |
dc.institutionauthor | Kaya A. | |
dc.institutionauthor | Kaya, Ayşe Demet | |
dc.institutionauthor | Yıldırım, Pınar | |
dc.institutionauthor | Kaya, Ayşe Demet | |
dc.language.iso | en | |
dc.publisher | Elsevier | en_US |
dc.relation.ispartof | 10th 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, BELGIUM | en_US |
dc.relation.ispartofseries | Procedia Computer Science | |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.scopus.citedbyCount | 0 | |
dc.subject | Biomedical Data Mining | en_US |
dc.subject | clustering | en_US |
dc.subject | k-means algorithm | en_US |
dc.subject | drug side effects | en_US |
dc.subject | WebMD | en_US |
dc.title | Clustering of Phentermine HCL Drug from Online Patient Medication Reviews | en_US |
dc.type | Conference Object | en_US |
dc.wos.citedbyCount | 0 | |
dspace.entity.type | Publication | |
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