Title Information
Title
Unsupervised induction of domain-specific semantic frames from operative notes for surgical clinical research
Name: Personal
Name Part
Wang, Yan
Role
Role Term: Text (marcrelator)
author
Name: Personal
Name Part
Pakhomov, Serguei
Role
Role Term: Text (marcrelator)
author
Name: Personal
Name Part
Melton, Genevieve B.
Role
Role Term: Text (marcrelator)
author
Type of Resource
text
Genre (Local)
poster abstracts
Origin Information
Date Created (keyDate="yes", encoding="w3cdtf")
2015
Language
Language Term: Code (ISO639-2B)
eng
Note (displayLabel="Source")
Electronic Health Record
Note (displayLabel="Method")
Natural Language Processing
Abstract
Surgical clinical research often utilizes information within operative notes including data about the supplies, tools, and techniques used for a given procedure. We have previously demonstrated that compared to general English semantic frames, surgical operative notes contain semantic frames with additional or different arguments and that additional verb senses. In this study, we investigated the use of an unsupervised approach for inducing semantic frames for surgical action verbs. Our results demonstrate that semantic frames induced from domain corpus using unsupervised approach cover most of the domain semantic frames created by human experts
Note: funding
Support for this research came from American Surgical Association Foundation and National Institutes of Health (#R01LM011364(GM), #R01GM102282(SP), #8UL1TR000114).
Note
Poster abstract for the 2015 AMIA Annual Symposium
Related Item: Host (displayLabel="Published in")
Title Information
Title
AMIA Joint Summits on Translational Science Proceedings
Origin Information
Date Created
2015
Date Created (keyDate="yes", encoding="w3cdtf")
2015
Physical Description
Extent
p. 415-416
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