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

Processing free-text clinical information in an electronic medical record (EMR) may enhance surveillance systems for early identification of ILI outbreaks. However, processing clinical text using 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.

Objective

To review the natural language processing (NLP) and technical challenges encountered in an automated influenza-like illness (ILI) surveillance system.