Adopting graph traversal techniques for context-driven value sets extraction from biomedical knowledge sources

Jyotishman Pathak, Guoqian D Jiang, Sridhar O. Dwarkanath, James D. Buntrock, Christopher G. Chute

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

The ability to model, share and re-use value sets across multiple medical information systems is an important requirement. However, generating value sets semi-automatically from, a terminology service is still an unresolved issue, in part due to the lack of linkage to clinical context patterns that provide the constraints in defining a concept domain and invocation of value sets extraction. Towards this goal, we develop and evaluate an approach for context-driven automatic value sets extraction based on a formal terminology model. The crux of the technique is to identify and define the context patterns from various domains of discourse and leverage them for value set extraction using two complementary ideas based on (i) local terms provided by the subject matter experts (extensional) and (ii) semantic definition of the concepts in coding schemes (intensional). We develop algorithms based on wellstudied graph traversal and ontology segmentation techniques for both the approaches and, implement a prototype demonstrating their applicability on use cases from SNOMED CT rendered in the LexGrid terminology model. We also present preliminary evaluation of our approach and report investigation results done by subject matter experts at the Mayo Clinic.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE International Conference on Semantic Computing 2008, ICSC 2008
Pages460-467
Number of pages8
DOIs
StatePublished - 2008
Event2nd Annual IEEE International Conference on Semantic Computing, ICSC 2008 - Santa Clara, CA, United States
Duration: Aug 4 2008Aug 7 2008

Other

Other2nd Annual IEEE International Conference on Semantic Computing, ICSC 2008
CountryUnited States
CitySanta Clara, CA
Period8/4/088/7/08

Fingerprint

Terminology
Medical information systems
Ontology
Semantics

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software

Cite this

Pathak, J., Jiang, G. D., Dwarkanath, S. O., Buntrock, J. D., & Chute, C. G. (2008). Adopting graph traversal techniques for context-driven value sets extraction from biomedical knowledge sources. In Proceedings - IEEE International Conference on Semantic Computing 2008, ICSC 2008 (pp. 460-467). [4597226] https://doi.org/10.1109/ICSC.2008.76

Adopting graph traversal techniques for context-driven value sets extraction from biomedical knowledge sources. / Pathak, Jyotishman; Jiang, Guoqian D; Dwarkanath, Sridhar O.; Buntrock, James D.; Chute, Christopher G.

Proceedings - IEEE International Conference on Semantic Computing 2008, ICSC 2008. 2008. p. 460-467 4597226.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Pathak, J, Jiang, GD, Dwarkanath, SO, Buntrock, JD & Chute, CG 2008, Adopting graph traversal techniques for context-driven value sets extraction from biomedical knowledge sources. in Proceedings - IEEE International Conference on Semantic Computing 2008, ICSC 2008., 4597226, pp. 460-467, 2nd Annual IEEE International Conference on Semantic Computing, ICSC 2008, Santa Clara, CA, United States, 8/4/08. https://doi.org/10.1109/ICSC.2008.76
Pathak J, Jiang GD, Dwarkanath SO, Buntrock JD, Chute CG. Adopting graph traversal techniques for context-driven value sets extraction from biomedical knowledge sources. In Proceedings - IEEE International Conference on Semantic Computing 2008, ICSC 2008. 2008. p. 460-467. 4597226 https://doi.org/10.1109/ICSC.2008.76
Pathak, Jyotishman ; Jiang, Guoqian D ; Dwarkanath, Sridhar O. ; Buntrock, James D. ; Chute, Christopher G. / Adopting graph traversal techniques for context-driven value sets extraction from biomedical knowledge sources. Proceedings - IEEE International Conference on Semantic Computing 2008, ICSC 2008. 2008. pp. 460-467
@inproceedings{28b56d6001594cf2b6225178c662d692,
title = "Adopting graph traversal techniques for context-driven value sets extraction from biomedical knowledge sources",
abstract = "The ability to model, share and re-use value sets across multiple medical information systems is an important requirement. However, generating value sets semi-automatically from, a terminology service is still an unresolved issue, in part due to the lack of linkage to clinical context patterns that provide the constraints in defining a concept domain and invocation of value sets extraction. Towards this goal, we develop and evaluate an approach for context-driven automatic value sets extraction based on a formal terminology model. The crux of the technique is to identify and define the context patterns from various domains of discourse and leverage them for value set extraction using two complementary ideas based on (i) local terms provided by the subject matter experts (extensional) and (ii) semantic definition of the concepts in coding schemes (intensional). We develop algorithms based on wellstudied graph traversal and ontology segmentation techniques for both the approaches and, implement a prototype demonstrating their applicability on use cases from SNOMED CT rendered in the LexGrid terminology model. We also present preliminary evaluation of our approach and report investigation results done by subject matter experts at the Mayo Clinic.",
author = "Jyotishman Pathak and Jiang, {Guoqian D} and Dwarkanath, {Sridhar O.} and Buntrock, {James D.} and Chute, {Christopher G.}",
year = "2008",
doi = "10.1109/ICSC.2008.76",
language = "English (US)",
isbn = "9780769532790",
pages = "460--467",
booktitle = "Proceedings - IEEE International Conference on Semantic Computing 2008, ICSC 2008",

}

TY - GEN

T1 - Adopting graph traversal techniques for context-driven value sets extraction from biomedical knowledge sources

AU - Pathak, Jyotishman

AU - Jiang, Guoqian D

AU - Dwarkanath, Sridhar O.

AU - Buntrock, James D.

AU - Chute, Christopher G.

PY - 2008

Y1 - 2008

N2 - The ability to model, share and re-use value sets across multiple medical information systems is an important requirement. However, generating value sets semi-automatically from, a terminology service is still an unresolved issue, in part due to the lack of linkage to clinical context patterns that provide the constraints in defining a concept domain and invocation of value sets extraction. Towards this goal, we develop and evaluate an approach for context-driven automatic value sets extraction based on a formal terminology model. The crux of the technique is to identify and define the context patterns from various domains of discourse and leverage them for value set extraction using two complementary ideas based on (i) local terms provided by the subject matter experts (extensional) and (ii) semantic definition of the concepts in coding schemes (intensional). We develop algorithms based on wellstudied graph traversal and ontology segmentation techniques for both the approaches and, implement a prototype demonstrating their applicability on use cases from SNOMED CT rendered in the LexGrid terminology model. We also present preliminary evaluation of our approach and report investigation results done by subject matter experts at the Mayo Clinic.

AB - The ability to model, share and re-use value sets across multiple medical information systems is an important requirement. However, generating value sets semi-automatically from, a terminology service is still an unresolved issue, in part due to the lack of linkage to clinical context patterns that provide the constraints in defining a concept domain and invocation of value sets extraction. Towards this goal, we develop and evaluate an approach for context-driven automatic value sets extraction based on a formal terminology model. The crux of the technique is to identify and define the context patterns from various domains of discourse and leverage them for value set extraction using two complementary ideas based on (i) local terms provided by the subject matter experts (extensional) and (ii) semantic definition of the concepts in coding schemes (intensional). We develop algorithms based on wellstudied graph traversal and ontology segmentation techniques for both the approaches and, implement a prototype demonstrating their applicability on use cases from SNOMED CT rendered in the LexGrid terminology model. We also present preliminary evaluation of our approach and report investigation results done by subject matter experts at the Mayo Clinic.

UR - http://www.scopus.com/inward/record.url?scp=52149124335&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=52149124335&partnerID=8YFLogxK

U2 - 10.1109/ICSC.2008.76

DO - 10.1109/ICSC.2008.76

M3 - Conference contribution

SN - 9780769532790

SP - 460

EP - 467

BT - Proceedings - IEEE International Conference on Semantic Computing 2008, ICSC 2008

ER -