用于糖尿病的数据挖掘技术：一项系统综述。
Data-mining technologies for diabetes: a systematic review.
作者信息
Marinov Miroslav, Mosa Abu Saleh Mohammad, Yoo Illhoi, Boren Suzanne Austin
机构信息
Informatics Institute, University of Missouri, Columbia, Missouri, USA.
出版信息
J Diabetes Sci Technol. 2011 Nov 1;5(6):1549-56. doi: 10.1177/193229681100500631.
BACKGROUND
The objective of this study is to conduct a systematic review of applications of data-mining techniques in the field of diabetes research.
METHOD
We searched the MEDLINE database through PubMed. We initially identified 31 articles by the search, and selected 17 articles representing various data-mining methods used for diabetes research. Our main interest was to identify research goals, diabetes types, data sets, data-mining methods, data-mining software and technologies, and outcomes.
RESULTS
The applications of data-mining techniques in the selected articles were useful for extracting valuable knowledge and generating new hypothesis for further scientific research/experimentation and improving health care for diabetes patients. The results could be used for both scientific research and real-life practice to improve the quality of health care diabetes patients.
CONCLUSIONS
Data mining has played an important role in diabetes research. Data mining would be a valuable asset for diabetes researchers because it can unearth hidden knowledge from a huge amount of diabetes-related data. We believe that data mining can significantly help diabetes research and ultimately improve the quality of health care for diabetes patients.
背景
本研究的目的是对数据挖掘技术在糖尿病研究领域的应用进行系统综述。
方法
我们通过PubMed搜索MEDLINE数据库。通过搜索最初识别出31篇文章，并选择了17篇代表用于糖尿病研究的各种数据挖掘方法的文章。我们主要关注的是确定研究目标、糖尿病类型、数据集、数据挖掘方法、数据挖掘软件和技术以及结果。
结果
所选文章中数据挖掘技术的应用有助于提取有价值的知识，并为进一步的科学研究/实验生成新的假设，以及改善糖尿病患者的医疗保健。这些结果可用于科学研究和实际生活实践，以提高糖尿病患者的医疗保健质量。
结论
数据挖掘在糖尿病研究中发挥了重要作用。数据挖掘对糖尿病研究人员来说将是一项宝贵资产，因为它可以从大量与糖尿病相关的数据中挖掘出隐藏的知识。我们相信数据挖掘可以显著帮助糖尿病研究，并最终提高糖尿病患者的医疗保健质量。
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