Zaruhi R. Mnatsakanyan

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INTRODUCTION Public health surveillance systems need to be refined. We intend to use a generic approach for early identification of patients with severe influenza-like illness (ILI) by calculating a score that estimates a patients disease-severity. Accordingly, we built the Intelligent Severity Score Estimation Model (ISSEM), structured so that the(More)
Radiology and public health have an emerging opportunity to collaborate, in which radiology's vast supply of imaging data can be integrated into public health information systems for epidemiologic assessments and responses to population health problems. Fueling the linkage of radiology and public health include (i) the transition from analog film to digital(More)
This study introduces new information fusion algorithms to enhance disease surveillance systems with Bayesian decision support capabilities. A detection system was built and tested using chief complaints from emergency department visits, International Classification of Diseases Revision 9 (ICD-9) codes from records of outpatient visits to civilian and(More)
This paper describes the problem of public health monitoring for waterborne disease outbreaks using disparate evidence from health surveillance data streams and environmental sensors. We present a combined monitoring approach along with examples from a recent project at the Johns Hopkins University Applied Physics Laboratory in collaboration with the U.S.(More)
ith an increasing concern over emerging infectious diseases, efficient and reliable public health monitoring is critical. The prototype models described in this article were built to aid public health officials in monitoring the health of their communities by increasing situational awareness and reducing false-positive identification of disease outbreaks.(More)
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