Titlebook: Biosurveillance and Biosecurity; International Worksh Daniel Zeng,Hsinchun Chen,Bill Lober Conference proceedings 2008 Springer-Verlag Berl

閘門

書目名稱Biosurveillance and Biosecurity影響因子(影響力)




書目名稱Biosurveillance and Biosecurity影響因子(影響力)學(xué)科排名




書目名稱Biosurveillance and Biosecurity網(wǎng)絡(luò)公開度




書目名稱Biosurveillance and Biosecurity網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Biosurveillance and Biosecurity被引頻次




書目名稱Biosurveillance and Biosecurity被引頻次學(xué)科排名




書目名稱Biosurveillance and Biosecurity年度引用




書目名稱Biosurveillance and Biosecurity年度引用學(xué)科排名




書目名稱Biosurveillance and Biosecurity讀者反饋




書目名稱Biosurveillance and Biosecurity讀者反饋學(xué)科排名

thrombosis

crescendo

情愛

accordance

Public Health Preparedness Informatics Infrastructure. A Case Study in Integrated Surveillance and Ralerting, situational awareness, emergency planning and response, resource assessment and management. These systems are optimized when embedded within an informatics framework supporting a community of information trading partners engaged in routine health information exchange. Seasonal influenza (f

女上癮

Dynamic Network Model for Predicting Occurrences of Salmonella at Food Facilitiesurrence data between USDA-controlled food processing establishments and various strains of Salmonella (serotypes) as a network which evolves over time. We apply a latent space model originally developed for dynamic analysis of social networks to predict the future link structure of the graph. Experi

外科醫(yī)生

Network-Based Analysis of Beijing SARS Data were constructed and analyzed, including the patient contact network, the weighted location (district) network, and the weighted occupation network. We demonstrate that a network-based data analysis framework can help evaluate various control strategies. For instance, in the case of SARS, a general

賞錢

沙漠

Onerous

A Temporal Extension of the Bayesian Aerosol Release Detectorization of outdoor aerosol releases of .. Recent research has shown promising results of early detection using Bayesian inference from syndromic data in conjunction with meteorological and geographical data [1]. Here we propose an extension of this algorithm that models multiple days of syndromic da