Literature DB >> 20351863

Methodology to develop and evaluate a semantic representation for NLP.

Jeannie Y Irwin1, Henk Harkema, Lee M Christensen, Titus Schleyer, Peter J Haug, Wendy W Chapman.   

Abstract

Natural language processing applications that extract information from text rely on semantic representations. The objective of this paper is to describe a methodology for creating a semantic representation for information that will be automatically extracted from textual clinical records. We illustrate two of the four steps of the methodology in this paper using the case study of encoding information from dictated dental exams: (1) develop an initial representation from a set of training documents and (2) iteratively evaluate and evolve the representation while developing annotation guidelines. Our approach for developing and evaluating a semantic representation is based on standard principles and approaches that are not dependent on any particular domain or type of semantic representation.

Mesh:

Year:  2009        PMID: 20351863      PMCID: PMC2815383     

Source DB:  PubMed          Journal:  AMIA Annu Symp Proc        ISSN: 1559-4076


  5 in total

1.  Classifying free-text triage chief complaints into syndromic categories with natural language processing.

Authors:  Wendy W Chapman; Lee M Christensen; Michael M Wagner; Peter J Haug; Oleg Ivanov; John N Dowling; Robert T Olszewski
Journal:  Artif Intell Med       Date:  2005-01       Impact factor: 5.326

2.  Clinical computing in general dentistry.

Authors:  Titus K L Schleyer; Thankam P Thyvalikakath; Heiko Spallek; Miguel H Torres-Urquidy; Pedro Hernandez; Jeannie Yuhaniak
Journal:  J Am Med Inform Assoc       Date:  2006-02-24       Impact factor: 4.497

3.  Evaluation of a semantic data model for chest radiology: application of a new methodology.

Authors:  R A Rocha; S M Huff; P J Haug; D A Evans; B E Bray
Journal:  Methods Inf Med       Date:  1998-11       Impact factor: 2.176

4.  The CLEF corpus: semantic annotation of clinical text.

Authors:  Angus Roberts; Robert Gaizauskas; Mark Hepple; Neil Davis; George Demetriou; Yikun Guo; Jay Kola; Ian Roberts; Andrea Setzer; Archana Tapuria; Bill Wheeldin
Journal:  AMIA Annu Symp Proc       Date:  2007-10-11

5.  Speech recognition in dental software systems: features and functionality.

Authors:  Jeannie Yuhaniak Irwin; Shawn Fernando; Titus Schleyer; Heiko Spallek
Journal:  Stud Health Technol Inform       Date:  2007
  5 in total
  5 in total

1.  Subgraph augmented non-negative tensor factorization (SANTF) for modeling clinical narrative text.

Authors:  Yuan Luo; Yu Xin; Ephraim Hochberg; Rohit Joshi; Ozlem Uzuner; Peter Szolovits
Journal:  J Am Med Inform Assoc       Date:  2015-04-09       Impact factor: 4.497

2.  Extending SemRep to the Public Health Domain.

Authors:  Graciela Rosemblat; Melissa P Resnick; Ione Auston; Dongwook Shin; Charles Sneiderman; Marcelo Fizsman; Thomas C Rindflesch
Journal:  J Am Soc Inf Sci Technol       Date:  2013-10

3.  A methodology for extending domain coverage in SemRep.

Authors:  Graciela Rosemblat; Dongwook Shin; Halil Kilicoglu; Charles Sneiderman; Thomas C Rindflesch
Journal:  J Biomed Inform       Date:  2013-08-21       Impact factor: 6.317

Review 4.  Current state of dental informatics in the field of health information systems: a scoping review.

Authors:  Ballester Benoit; Bukiet Frédéric; Dufour Jean-Charles
Journal:  BMC Oral Health       Date:  2022-04-19       Impact factor: 3.747

5.  A common type system for clinical natural language processing.

Authors:  Stephen T Wu; Vinod C Kaggal; Dmitriy Dligach; James J Masanz; Pei Chen; Lee Becker; Wendy W Chapman; Guergana K Savova; Hongfang Liu; Christopher G Chute
Journal:  J Biomed Semantics       Date:  2013-01-03
  5 in total

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