{"title":"On the Analysis of a Public Dataset for Diabetes","authors":"Abdihakim Mao, M. O. Shafiq","doi":"10.1109/ICDIM.2018.8847123","DOIUrl":null,"url":null,"abstract":"Analyzing data by visualization can help medical institutions make more informed decisions on the admission of future patients. A dataset provided by the University of California, Irvine, (UCI) Machine Learning Repository contains information on patients with diabetes that represents 10 years (1999-2008) of clinical care at 130 US hospitals. Charts on the diabetes dataset were created using Tableau, a data visualization software. In addition, an extensive analysis of the dataset was completed by providing possible reasons for the output found in the charts. The knowledge obtained from analyzing the diabetes dataset will help provide important information to medical institutions concerning future diabetic patients in need of hospital services.","PeriodicalId":120884,"journal":{"name":"2018 Thirteenth International Conference on Digital Information Management (ICDIM)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Thirteenth International Conference on Digital Information Management (ICDIM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDIM.2018.8847123","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Analyzing data by visualization can help medical institutions make more informed decisions on the admission of future patients. A dataset provided by the University of California, Irvine, (UCI) Machine Learning Repository contains information on patients with diabetes that represents 10 years (1999-2008) of clinical care at 130 US hospitals. Charts on the diabetes dataset were created using Tableau, a data visualization software. In addition, an extensive analysis of the dataset was completed by providing possible reasons for the output found in the charts. The knowledge obtained from analyzing the diabetes dataset will help provide important information to medical institutions concerning future diabetic patients in need of hospital services.