Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

Effectiveness of lexico-syntactic pattern matching for ontology enrichment with clinical documents

Liu, K and Chapman, WW and Savova, G and Chute, CG and Sioutos, N and Crowley, RS (2011) Effectiveness of lexico-syntactic pattern matching for ontology enrichment with clinical documents. Methods of Information in Medicine, 50 (5). 397 - 407. ISSN 0026-1270

[img] Plain Text (licence)
Available under License : See the attached license file.

Download (1kB)

Abstract

Objective: To evaluate the effectiveness of a lexico-syntactic pattern (LSP) matching method for ontology enrichment using clinical documents. Methods: Two domains were separately studied using the same methodology. We used radiology documents to enrich RadLex and pathology documents to enrich National Cancer Institute Thesaurus (NCIT). Several known LSPs were used for semantic knowl - edge extraction. We first retrieved all sentences that contained LSPs across two large clinical repositories, and examined the frequency of the LSPs. From this set, we randomly sampled LSP instances which were examined by human judges. We used a two-step method to determine the utility of these patterns for enrichment. In the first step, domain experts annotated medically meaningful terms (MMTs) from each sentence within the LSP. In the second step, RadLex and NCIT curators evaluated how many of these MMTs could be added to the resource. To quantify the utility of this LSP method, we defined two evaluation metrics: suggestion rate (SR) and acceptance rate (AR). We used these measures to estimate the yield of concepts and relationships, for each of the two domains. Results: For NCIT, the concept SR was 24%, and the relationship SR was 65%. The concept AR was 21%, and the relationship AR was 14%. For RadLex, the concept SR was 37%, and the relationship SR was 55%. The concept AR was 11%, and the relationship AR was 44%. Conclusion: The LSP matching method is an effective method for concept and concept relationship discovery in biomedical domains. © Schattauer 2011.


Share

Citation/Export:
Social Networking:
Share |

Details

Item Type: Article
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Liu, K
Chapman, WW
Savova, G
Chute, CG
Sioutos, N
Crowley, RS
Date: 19 December 2011
Date Type: Publication
Journal or Publication Title: Methods of Information in Medicine
Volume: 50
Number: 5
Page Range: 397 - 407
DOI or Unique Handle: 10.3414/me10-01-0020
Schools and Programs: School of Medicine > Biomedical Informatics
Refereed: Yes
ISSN: 0026-1270
MeSH Headings: Artificial Intelligence; Humans; Learning; Medical Informatics; National Cancer Institute (U.S.); Natural Language Processing; Pathology, Surgical--instrumentation; Radiology--instrumentation; Semantics; Terminology as Topic; United States
Other ID: NLM NIHMS268178, NLM PMC3125434
PubMed Central ID: PMC3125434
PubMed ID: 21057720
Date Deposited: 29 Aug 2012 21:06
Last Modified: 03 Feb 2019 00:55
URI: http://d-scholarship.pitt.edu/id/eprint/13823

Metrics

Monthly Views for the past 3 years

Plum Analytics

Altmetric.com


Actions (login required)

View Item View Item