摘要
为实现糖尿病的早期筛查,提高对糖尿病分类的准确度,在研究有关糖尿病危险因素的基础上,增加糖化血红蛋白作为糖尿病早期筛查的特征之一。研究中选取与人类最为相似的食蟹猴作为研究对象,利用年龄、血压、腹围、BMI、糖化血红蛋白以及空腹血糖作为特征输入,将正常、糖尿病前期和糖尿病作为类别输出,利用K-Nearest Neighbor(KNN)和神经网络两种方法对其分类。发现在增加糖化血红蛋白作为分类特征之一时,KNN(K=3)和神经网络的分类准确率分别为81.8%和92.6%,明显高于没有这一特征时的准确率(68.1%和89.7%),KNN和神经网络都可以对食蟹猴数据进行分类和识别,起到早期筛查作用。
In order to achieve the early screening for diabetes and improve the accuracy of classification of diabetes,on the basis of studying the risk factors of diabetes,glycosylated hemoglobin is added as one of the features in the early screening for diabetes.Herein cynomolgus monkeys that are most similar to humans were selected as the study subjects.Several features,such as age,blood pressure,abdominal circumference,body mass index,glycated hemoglobin and fasting blood glucose,are chosen as inputs,while normal,prediabetes and diabetes are output as categories.Both K-Nearest Neighbor(KNN)and neural network are used to classify diabetes.When glycosylated hemoglobin is added as one of the classification features,the accuracy of classification using KNN(K=3)and neural network is 81.8%and 92.6%,respectively,significantly higher than the accuracy which is obtained without considering the feature of glycosylated hemoglobin(68.1%and 89.7%).Therefore,both KNN and neural network can classify and identify the data of cynomolgus monkey and achieve an early screening for diabetes.
作者
陈真诚
杜莹
邹春林
梁永波
吴植强
朱健铭
CHEN Zhencheng;DU Ying;ZOU Chunlin;LIANG Yongbo;WU Zhiqiang;ZHU Jianming(School of Life and Environmental Sciences,Guilin University of Electronic Technology,Guilin 541004,China;School of Electronic Engineering and Automation,Guilin University of Electronic Technology,Guilin 541004,China;Transforming Medical Research Center,Guangxi Medical University,Nanning 530021,China;Medical Devices Testing Center of Guangxi Zhuang Autonomous Region,Nanning 530021,China)
出处
《中国医学物理学杂志》
CSCD
2018年第10期1220-1224,共5页
Chinese Journal of Medical Physics
基金
国家自然科学基金重大科研仪器研制项目(61627807)
广西自然科学基金(2017GXNSFGA198005)
广西自然科学基金青年基金(2016GXNSFBA380145)
国家重点研发计划课题(2016YFC1305703)
广西自动检测技术与仪器重点实验室主任基金(YQ17118)
广西信息科学实验中心一般项目(YB1513)
关键词
糖尿病
糖化血红蛋白
空腹血糖
KNN
神经网络
食蟹猴
diabetes
glycosylated hemoglobin
fasting blood glucose
K-Nearest Neighbor
neural network
cynomolgus monkey
