Displaying results 1 - 4 of 4
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Extracting Surveillance Data from Templated Sections of an Electronic Medical Note: Challenges and Opportunities
Content Type: Abstract
The main stay of recording patient data is the free text of electronic medical records (EMR). While stating the chief complaint and history of presenting illness in the patients ‘own words’, the rest of the electronic note is written by the provider… read more -
Finding medically unexplained symptoms within VA clinical documents using v3NLP
Content Type: Abstract
Pro-WATCH (protecting war fighters using algorithms for text processing to capture health events), a syndromic surveillance project for veterans of operation enduring freedom (OEF)/operation Iraqi freedom (OIF), includes a task to identify medically… read more -
Using clinician mental models to guide annotation of medically unexplained symptoms and syndromes found in VA clinical documents
Content Type: Abstract
Medically unexplained syndromes (MUS) are conditions that are diagnosed on the basis of symptom constellations and are characterized by a lack of well-defined pathogenic pathways. The three most common MUS are chronic fatigue … read more -
Standardization to aid interoperability between NLP system
Content Type: Abstract
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… read more