On the Analysis of a Public Dataset for Diabetes

Abdihakim Mao, M. O. Shafiq
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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.
关于糖尿病公共数据集的分析
通过可视化分析数据可以帮助医疗机构对未来患者的入院做出更明智的决定。加州大学欧文分校(UCI)机器学习存储库提供的数据集包含了美国130家医院10年(1999-2008)临床护理的糖尿病患者信息。糖尿病数据集上的图表是使用数据可视化软件Tableau创建的。此外,通过提供图表中发现的输出的可能原因,完成了对数据集的广泛分析。通过分析糖尿病数据集获得的知识将有助于为医疗机构提供有关未来需要医院服务的糖尿病患者的重要信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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