| 基于传感器聚类数据挖掘的物联网智慧医疗模型设计 |
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| 引用本文： | 黄辰,潘永才李可维等.基于传感器聚类数据挖掘的物联网智慧医疗模型设计[J].传感器与微系统,2014(4):76-79. |
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| 作者姓名： | 黄辰 潘永才李可维等 |
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| 作者单位： | [1]湖北大学计算机与信息工程学院,湖北武汉430062 [2]武汉第二船舶设计研究所,湖北武汉430064 [3]华中科技大学电子与信息工程系,湖北武汉430074 |
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| 基金项目： | 国家自然科学基金资助项目（61201254）;湖北省软科学物联网产业发展专项项目（2011DHA014）;教育部大学生创新创业计划资助项目（201210512004） |
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| 摘 要： | 现代智慧医疗需要操作简洁、反应迅速,能够提供智慧诊断的信息化平台,提出基于物联网无线传感器技术的智慧医疗模型。系统利用附着在患者身上的各类传感器采集到的生理信息数据,采用基于密度的带有噪声的空间聚类(DBSCAN)算法的数据分析方法,用非线性映射把患者的生理信息数据转换到高纬度的特征空间,对变换后的矢量数据进行聚类分析,从而提升聚类结果并有效辅助医务人员进行诊断。
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| 关 键 词： | 物联网 智慧医疗 基于密度的带有噪声的空间聚类算法 |
Design of intelligent medical model based on sensor clustering data mining in IoT |
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| HUANG Chen,PAN Yong-cai,LI Ke-wei,HUANG Ben-xiong,PI Jian-fu,FU Yong-qian.Design of intelligent medical model based on sensor clustering data mining in IoT[J].Transducer and Microsystem Technology,2014(4):76-79. |
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| Authors: | HUANG Chen PAN Yong-cai LI Ke-wei HUANG Ben-xiong PI Jian-fu FU Yong-qian |
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| Affiliation: | 1.School of Computer and Information Engineering, Hubei University, Wuhan 430062, China; 2.Wuhan Second Ship Design and Research Institute, Wuhan 430064, China; 3.Department of Electronic and Information Engineering, Huazhong University of Science and Technology,Wuhan 430074, China;) |
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| Abstract: | Modern intelligent medical care needs an information platform which can provide easy operation,fast response,and intellective diagnose,so propose intelligent medical model based on Internet of things （IoT） wireless sensor technology.This system collects physiological datas by intelligent sensors attached to patients,and adopts data analysis method based on density clustering density-based spatial clustering of applications with noise （DBSCAN） algorithm using space transformation,which converts physiological information to a high dimension feature space using nonlinear mapping,and carry out clustering analysis on transformed vector data,to promote clustering efficiency and assist medical staffs to diagnose. |
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| Keywords: | Internet of things （IoT） intelligent medical density-based spatial clustering of applications with noise （DBSCAN） algorithm |
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