Displaying results 1 - 3 of 3
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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… being customized to identify symptoms within VA clinical documents, and then refined to assign duration. The … symptoms and the aggregation of this information across documents by patient’s is not addressed here. Objective … the parts of speech and words around medical concepts, document type and section headings. For this Pro-WATCH task, … -
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… consistently applied to identify MUS found in VA clinical documents. These efforts will support building a … to 3314, with an average of 17 symptom annotations per document. The number of annotations (unique mentions) for … -
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… IE tools, corpus evaluation tools and encoded clinical documents. There are two components to a successful … community, yet be expressive enough to encode a clinical document, a named entity, relationships between entities, …