Natural Language Processing and Technical Challenges of Influenza-Like Illness Surveillance
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How to Cite

Rumoro, D. P., Gibbs, G. S., Shah, S. C., Hallock, M. M., Trenholme, G. M., Waddell, M. J., & Bernstein, J. P. (2016). Natural Language Processing and Technical Challenges of Influenza-Like Illness Surveillance. Online Journal of Public Health Informatics, 8(1). https://doi.org/10.5210/ojphi.v8i1.6575

Abstract

Processing free-text clinical information in an electronic medical record may enhance surveillance systems for early identification of influenza-like illness outbreaks. However, processing clinical text using natural language processing (NLP) poses a challenge in preserving the semantics of the original information recorded. In this study, we discuss several NLP and technical issues as well as potential solutions for implementation in syndromic surveillance systems.

https://doi.org/10.5210/ojphi.v8i1.6575
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