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

  • Xi Meng
  • Ji-Jiang Yang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8549)

Abstract

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.

Keywords

T2DM visualization visual analysis co-word MDS 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Xi Meng
    • 1
  • Ji-Jiang Yang
    • 2
    • 3
  1. 1.Department of Public Security Intelligence SciencePeople’ Public Security University of ChinaBeijingChina
  2. 2.RIITTsinghua UniversityBeijingChina
  3. 3.TNListTsinghua UniversityBeijingChina

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