An infectious disease/fever screening radar system which stratifies higher-risk patients within ten seconds using a neural network and the fuzzy grouping method.
An infectious disease/fever screening radar system which stratifies higher-risk patients within ten seconds using a neural network and the fuzzy grouping method.
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DOI：
10.1016/j.jinf.2014.12.007
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发表时间：
2015-03
期刊：
影响因子：
--
通讯作者：
Abe S
中科院分区：
文献类型：
--
作者：
Sun G;Matsui T;Hakozaki Y;Abe S
为了在10秒内对流感高危患者进行分类，我们开发了传染病和发热筛查雷达系统。该系统根据生命体征筛选感染患者，即雷达测量的呼吸频率，指尖光反射器测量的心率，以及热像仪测量的面部温度。该系统使用神经网络和模糊聚类方法（FCM）将受试者分为高危流感（HR-I）组、低危流感（LR-I）组和非流感（Non-I）组。我们对日本自卫队中心医院的35名季节性流感患者和48名正常对照进行了流感筛查。测定脉搏血氧饱和度（SpO2）作为参考。系统将17例受试者分为HR-I组，26例分为LR-I组，40例分为Non-I组。17例HR-I患者中有10例SpO2 <96%，而26例LR-I患者中只有2例SpO2 <96%。卡方检验显示，hr - 1组与lr - 1组SpO2 <96%的受试者比例差异有统计学意义（p < 0.001）。HR-I组和LR-I组分别有0例和9例正常对照，Non-I组有1例流感患者。神经网络与FCM相结合，可在10 s内有效检测出96% SpO2的高危流感患者。一种新型传染病/发热筛查雷达系统在10秒内对高危患者进行分层。利用最优神经网络和模糊聚类方法对多维生命体征数据进行分类。该系统可用于预防传染病暴发期间医生的二次暴露。该系统有潜力成为快速大规模筛查传染病的有用工具。
To classify higher-risk influenza patients within 10 s, we developed an infectious disease and fever screening radar system. The system screens infected patients based on vital signs, i.e., respiration rate measured by a radar, heart rate by a finger-tip photo-reflector, and facial temperature by a thermography. The system segregates subjects into higher-risk influenza (HR-I) group, lower-risk influenza (LR-I) group, and non-influenza (Non-I) group using a neural network and fuzzy clustering method (FCM). We conducted influenza screening for 35 seasonal influenza patients and 48 normal control subjects at the Japan Self-Defense Force Central Hospital. Pulse oximetry oxygen saturation (SpO2) was measured as a reference. The system classified 17 subjects into HR-I group, 26 into LR-I group, and 40 into Non-I group. Ten out of the 17 HR-I subjects indicated SpO2 <96%, whereas only two out of the 26 LR-I subjects showed SpO2 <96%. The chi-squared test revealed a significant difference in the ratio of subjects showed SpO2 <96% between HR-I and LR-I group (p < 0.001). There were zero and nine normal control subjects in HR-I and LR-I groups, respectively, and there was one influenza patient in Non-I group. The combination of neural network and FCM achieved efficient detection of higher-risk influenza patients who indicated SpO2 96% within 10 s. A novel infectious disease/fever screening radar system stratifies higher-risk patients within ten seconds. Use of an optimal neural network and the fuzzy clustering method to classify multiple-dimensional vital signs data. The system can be used for preventing secondary exposure of physicians during outbreaks of infectious disease. The system has potential to serve as a helpful tool for rapid mass screening of infectious disease.
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影响因子：
3.7
作者：
Nishiura H;Kamiya K
通讯作者：
Kamiya K
人类感染新型禽源甲型流感 (H7N9) 病毒。
影响因子：
158.5
作者：
Gao, Rongbao;Cao, Bin;Shu, Yuelong
通讯作者：
Shu, Yuelong
DOI：
10.1016/j.jinf.2010.01.005
发表时间：
2010-04
期刊：
The Journal of infection
影响因子：
--
作者：
Matsui T;Hakozaki Y;Suzuki S;Usui T;Kato T;Hasegawa K;Sugiyama Y;Sugamata M;Abe S
通讯作者：
Abe S
影响因子：
120.7
作者：
Thompson, WW;Shay, DK;Fukuda, K
通讯作者：
Fukuda, K
影响因子：
3.1
作者：
Ng, EYK;Kaw, GJL;Chang, WM
通讯作者：
Chang, WM