检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:刘璐 张春柯 颜建军[3] 郭睿[1] 王忆勤[1] 燕海霞[1] LIU Lu;ZHANG Chun-ke;YAN Jian-jun;GUO Rui;WANG Yi-qin;YAN Hai-xia(School of Basic Medical Sciences,Shanghai University of Traditional Chinese Medicine,Shanghai 201203,China;People's Hospital of Ganzhou District,Zhangye 734000,China;'School of Mechanical and Power Engineering,East China University of Science and Technology,Shanghai 200237,China)
机构地区:[1]上海中医药大学基础医学院,上海201203 [2]甘州区人民医院,张掖734000 [3]华东理工大学机械与动力工程学院,上海200237
出 处:《中华中医药杂志》2022年第11期6678-6681,共4页China Journal of Traditional Chinese Medicine and Pharmacy
基 金:国家自然科学基金面上项目(No.82074332,No.81673880);上海科学技术委员会生物医药领域项目(No.19441901100);上海市健康辨识与评估重点实验室(No.21DZ2271000)。
摘 要:目的:通过分析疑似冠心病患者中冠心病组与非冠心病组的脉图特征,并基于脉图特征建立冠心病高危人群筛查模型,挖掘脉诊的临床诊断价值。方法:将疑似冠心病患者分为冠心病组与非冠心病组,采用SmartTCM-I型脉象仪采集脉象样本,运用非参数检验统计方法比较两组脉图特征差异;采用随机森林模式识别算法,建立冠心病高危人群筛查模型。结果:与非冠心病组比较,冠心病组时域特征h2/h1、h3/h1显著增大(P<0.01);多尺度熵MSE1、MSE2、MSE3、MSE4、MSE5显著减小(P<0.05),当脉图时域特征和多尺度熵特征都参入建模时,模型性能最高,模型的准确度最高(95.67%)、特异度最高(93.99%)、误判率最低(6.01%)。结论:脉图特征一定程度上可以反映疑似冠心病患者病理状态及血管功能,基于脉图特征等信息建立的冠心病高危人群筛查模型具有一定的参考意义。Objective:By analyzing TCM pulse characteristics of suspected patients with coronary heart disease(CHD)and establishing the screening model of CHD high-risk population based on the pulse characteristics,the clinical diagnostic value of TCM was explore.Methods:The pulse samples were collected by Smart TCM-I digital pulse acquisition analyzer,which were divided into CHD group and non-CHD group,and the differences of characteristic parameters between the two groups were compared and analyzed by non-parametric test.Random forest pattern recognition algorithm was used to establish a screening model for high-risk population of CHD.Results:Compared with non-CHD group,the time-domain characteristics h2/h1 and h3/h1 in CHD group pulse were significantly increased(P<0.01).The multi-scale entropy MSE1,MSE2,MSE3,MSE4 and MSE5 decreased significantly(P<0.05).When the time-domain features and multi-scale entropy of pulse recordings were used in the modeling,the model has the highest performance,the highest recognition rate(95.67%),the highest specificity(93.99%)and the lowest misjudgment rate(6.01%).Conclusion:To a certain extent,the characteristics of pulse recordings can reflect the pathological state and vascular function of patients with suspected CHD.The screening model for high-risk population of CHD based on the characteristics has potential reference significance.
关 键 词:冠心病 脉图 时域参数 多尺度熵 随机森模式识别算法 冠心病高危人群筛查模型 脉诊
分 类 号:R541.4[医药卫生—心血管疾病]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.46