Visual Analysis for Type 2 Diabetes Mellitus - Based on Electronic Medical Records

被引：0
|
作者：
Meng, Xi [1 ]
Yang, Ji-Jiang [2 ,3 ]
机构：
[1] People Publ Secur Univ China, Dept Publ Secur Intelligence Sci, Beijing 100038, Peoples R China
[2] Tsinghua Univ, RIIT, Beijing 100084, Peoples R China
[3] Tsinghua Univ, TNList, Beijing 100084, Peoples R China
来源：
SMART HEALTH, ICSH 2014 | 2014年 / 8549卷
关键词：
T2DM; visualization; visual analysis; co-word; MDS; WORD ANALYSIS; LIFE-STYLE; CARE; DOCUMENTATION; PERSPECTIVES; DISEASE;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A multidimensional-scaling approach is proposed to analyze the main symptoms of T2DM. Based on 200 Type 2 diabetes patients' electronic medical records, the terms which were used to described symptoms in the records and their co-occurring query terms were analyzed. A distanced-based similarity measure was used to calculate the proximity of terms to one and another based on their co-occurrences in the 200 medical records. After the calculation of the distance between each two keywords, a visual clustering of groups of terms was conducted. Each terms distribution within each visual configuration showed the most common symptoms of Type 2 diabetes such as Foam in Urine, Intermittent Dizziness, Hyperlipemia, Feeble, Diuresis etc; however it also showed some hidden relations behind our cognition.
引用
收藏
页码：160 / +
页数：3
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