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首页> 外文期刊>BMC Medical Informatics and Decision Making >Estimation of hospital emergency room data using otc pharmaceutical sales and least mean square filters
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Estimation of hospital emergency room data using otc pharmaceutical sales and least mean square filters

机译：使用OTC药品销售和最小均方过滤器估算医院急诊室数据

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Background Surveillance of Over-the-Counter pharmaceutical (OTC) sales as a potential early indicator of developing public health conditions, in particular in cases of interest to Bioterrorism, has been suggested in the literature. The data streams of interest are quite non-stationary and we address this problem from the viewpoint of linear adaptive filter theory: the clinical data is the primary channel which is to be estimated from the OTC data that form the reference channels. Method The OTC data are grouped into a few categories and we estimate the clinical data using each individual category, as well as using a multichannel filter that encompasses all the OTC categories. The estimation (in the least mean square sense) is performed using an FIR (Finite Impulse Response) filter and the normalized LMS algorithm. Results We show all estimation results and present a table of effectiveness of each OTC category, as well as the effectiveness of the combined filtering operation. Individual group results clearly show the effectiveness of each particular group in estimating the clinical hospital data and serve as a guide as to which groups have sustained correlations with the clinical data. Conclusion Our results indicate that Multichannle adaptive FIR least squares filtering is a viable means of estimating public health conditions from OTC sales, and provide quantitative measures of time dependent correlations between the clinical data and the OTC data channels.
机译：背景技术文献中已经提出了对非处方药（OTC）销售的监视作为发展公共卫生状况的潜在早期指标，特别是在对生物恐怖主义感兴趣的情况下。感兴趣的数据流非常不稳定，因此我们从线性自适应滤波器理论的角度解决此问题：临床数据是主要通道，应从构成参考通道的OTC数据中估算出该通道。方法将OTC数据分为几个类别，我们使用每个单独的类别以及涵盖所有OTC类别的多通道过滤器来估计临床数据。估计（在最小均方意义上）是使用FIR（有限脉冲响应）滤波器和归一化LMS算法执行的。结果我们显示了所有估计结果，并列出了每种OTC类别的有效性以及组合过滤操作的有效性。各个组的结果清楚地表明了每个特定组在估计临床医院数据方面的有效性，并可以指导哪些组与临床数据具有持续的相关性。结论我们的结果表明，多通道自适应FIR最小二乘滤波是一种从OTC销售额估算公共卫生状况的可行方法，并且可提供定量的量度措施来衡量临床数据与OTC数据通道之间的时间相关性。

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