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

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.