机构：[1]The Second Clinical College, Guangzhou University of Chinese Medicine, Guangzhou, China广东省中医院[2]Department of Health Sciences Research, Mayo Clinic, Rochester, USA[3]University of Minnesota, Minneapolis, USA
The purpose of this study is to explore pathophysiological mechanisms present in patients that suffer from Chronic Kidney Disease complicated by Metabolic Syndrome (CKD-MetS) so as to better support proactive treatment. Association rule mining was applied to extract significant associations from the Semantic MEDLINE Database (SemMedDB). A total of 23,310 PMIDs with 5,542 unique items were included in our dataset. We focused on 5 specific syndromes that were extracted: diabetes, cardiovascular disease, increased triglycerides, obesity and inflammation. The number of rules generated for these five diseases are 80, 197, 31, 21 and 21 respectively. Our study identified several pathophysiological mechanisms that exist in CKD-MetS patients that can contribute to further renal damage.
基金：
Traditional Chinese Medicine Bureau of Guangdong Province, China [2015KT1535]; Guangzhou Science and Technology Program key projects [2016201604030022]; Guangdong Science and Technology Department [2014A020221087]; Guangdong Provincial Hospital of Chinese Medicine Program [2017KT1642]
语种：
外文
被引次数：
WOS：
第一作者：
第一作者机构：[1]The Second Clinical College, Guangzhou University of Chinese Medicine, Guangzhou, China[2]Department of Health Sciences Research, Mayo Clinic, Rochester, USA
通讯作者：
推荐引用方式(GB/T 7714)：
Peng Suyuan,Fan Yadan,Wang Liwei,et al.Leveraging Association Rule Mining to Detect Pathophysiological Mechanisms of Chronic Kidney Disease Complicated by Metabolic Syndrome[J].PROCEEDINGS 2018 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM).2018,1302-1309.
APA：
Peng, Suyuan,Fan, Yadan,Wang, Liwei,Wen, Andrew,Liu, Xusheng...&Shen, Feichen.(2018).Leveraging Association Rule Mining to Detect Pathophysiological Mechanisms of Chronic Kidney Disease Complicated by Metabolic Syndrome.PROCEEDINGS 2018 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM),,
MLA：
Peng, Suyuan,et al."Leveraging Association Rule Mining to Detect Pathophysiological Mechanisms of Chronic Kidney Disease Complicated by Metabolic Syndrome".PROCEEDINGS 2018 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM) .(2018):1302-1309
