Abstract

The present study represents an original approach to data interpretation of clinical data for patients with diagnosis diabetes mellitus type 2 (DMT2) using fuzzy clustering as a tool for intelligent data analysis. Fuzzy clustering is often used in classification and interpretation of medical data (including in medical diagnosis studies) but in this study it is applied with a different goal: to separate a group of 100 patients with DMT2 from a control group of healthy volunteers and, further, to reveal three different patterns of similarity between the patients. Each pattern is described by specific descriptors (variables), which ensure pattern interpretation by appearance of underling disease to DMT2.

摘要

本研究代表了使用模糊聚类作为智能数据分析工具来诊断2型糖尿病（DMT2）患者临床数据的原始方法。模糊聚类通常用于医学数据的分类和解释（包括医学诊断研究），但在本研究中，模糊聚类的应用目的不同：将100名DMT2患者与健康志愿者对照组分开，进一步，以揭示患者之间三种相似的不同模式。每个模式都由特定的描述符（变量）描述，这些描述符通过向DMT2展示基础疾病来确保模式解释。