Intelligent analysis of present lifestyle may help to understand the development of the chronic diseases and the relationship of these diseases together. It is possible to reduce or prevent the development of these diseases. In this work, a novel intelligent method is introduced and applied for early detection of type 2 diabetic. Intelligent analysis depends mainly on evaluation life-threatening conditions (obesity, hypertension, smoking status, alcohol drinking status and low level of physical activities) to extract knowledge from linguistic variablesand design a new cognitive tool to assist in the prediction process.This method consists from three stages: in the first stage, data was collected from 100 healthy volunteers, which includes evaluations of life-threatening conditions. The second stage is implementation of fuzzy model for early prediction of type 2 diabetes. Predicted blood glucose values of proposal technique were compared with average fasting blood glucose values based on analysis of Bland-Altman plot. Furthermore, fuzzy system model presents superior results (accuracy=81%, precision=0.57% and recall=0.83%).

对当前生活方式的智能分析可能有助于了解慢性病的发展以及这些疾病之间的关系。有可能减少或预防这些疾病的发展。在这项工作中，引入了一种新的智能方法并将其应用于2型糖尿病的早期检测。智能分析主要依靠评估威胁生命的状况（肥胖、高血压、吸烟状况、饮酒状况和低水平的体力活动）从语言变量中提取知识并设计一种新的认知工具来辅助预测过程。该方法包括三个阶段：在第一阶段，从 100 名健康志愿者那里收集数据，其中包括对危及生命的状况的评估。第二阶段是模糊模型的实施，用于 2 型糖尿病的早期预测。基于Bland-Altman图分析，将建议技术的预测血糖值与平均空腹血糖值进行比较。此外，模糊系统模型呈现出优异的结果（准确度=81%，精确度=0.57%，召回率=0.83%）。