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 … -
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… Divita et al.; licensee Emerging Health Threats Journal. www.eht-journal.org 21 Veterans Affairs has a real need to … 1–2 December 2010. References 1 Demner-Fushman D, Chapman WW, McDonald CJ. What can natural language processing do for … Annotation Workshop, ACL-IJCNLP 2009, pp 27–34. www.aclweb.org/anthol- ogy/W/W09/W09-3004.pdf. 3 Dolin R, … -
Identification of features for detection and prediction of homelessness from VA clinical documents
Content Type: Abstract
Homelessness in general is a major issue in the US today. The risk factors of homelessness are myriad, including inadequate income, lack of affordable housing, mental health and substance abuse issues, lack of social support, and nonadherence to… read more… S Shen et al.; licensee Emerging Health Threats Journal. www.eht-journal.org 63 …