Displaying results 1 - 3 of 3
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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… Language Processing system developed for automated symp- tom extraction. Our overarching goal is to characterize the … South et al.; licensee Emerging Health Threats Journal. www.eht-journal.org 64 unknown syndromes of interest to … Health Threats Journal BR South et al. 2011, 4:s115 www.eht-journal.org page 2/2 65 … -
Using NLP on VA Electronic Medical Records to Facilitate Epidemiologic Case Investigations
Content Type: Abstract
A major goal of biosurveillance is the timely detection of an infectious disease outbreak. Once a disease has been identified, another very important goal is to find all known cases of the disease to assist public health… read more… to structured data sources. References 1. Chapman WW, Bridewell W, Hanbury P, Cooper GF, Buchanan BG. A simple … -
Automated Detection of GI Syndrome using Structured and Non-Structured Data from the VA EMR
Content Type: Abstract
Objective We performed a gold-standard manual chart review for gastro-intestinal syndrome to evaluate automated detection models based on both structured and non-structured data extracted from the VA … read more… elements relevant to GI syndrome. REFERENCES 1. Chapman WW, Bridewell W, Hanbury P, Cooper GF, Buchanan BG. A simple …