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Challenges in adapting an natural language processing system for real-time surveillance


We are developing a Bayesian surveillance system for realtime surveillance and characterization of outbreaks that incorporates a variety of data elements, including free-text clinical reports. An existing natural language processing (NLP) system called Topaz is being used to extract clinical data from the reports. Moving the NLP system from a research project to a real-time service has presented many challenges.



Adapt an existing NLP system to be a useful component in a system performing real-time surveillance.

Submitted by hparton on