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Harkema Henk

There are a number of Natural Language Processing (NLP) annotation and Information Extraction (IE) systems and platforms that have been successfully used within the medical domain. Although these groups share components of their systems, there has not been a successful effort in the medical domain to codify and standardize either the syntax or semantics between systems to allow for interoperability between annotation tools, NLP tools, IE tools, corpus evaluation tools and encoded clinical documents. There are two components to a successful interoperability standard: an information and a semantic model.

Objective

The Consortium for Healthcare Informatics Research, a Department of Veterans Affairs (VA) Office of Research and Development is sponsoring the development of a standard ontology and information model for Natural Language Processing interoperability within the biomedical domain.

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Submitted by uysz on

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.

 

Objective

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

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Submitted by hparton on

Case detection from chief complaints suffers from low to moderate sensitivity. Emergency Department (ED) reports contain detailed clinical information that could improve case detection ability and enhance outbreak characterization. We developed a text processing system called Topaz that could be used to answer questions from ED reports, such as: How many new patients have come to the ED with acute lower respiratory symptoms? Of the respiratory patients, how many had a productive cough or wheezing? How many of the respiratory patients have a past history of asthma?

 

Objective

To evaluate how well a text processing system called Topaz can identify acute episodes of 55 clinical conditions described in ED notes.

Referenced File
Submitted by elamb on
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