Literature DB >> 12386114

Methods for semi-automated indexing for high precision information retrieval.

Daniel C Berrios1, Russell J Cucina, Lawrence M Fagan.   

Abstract

OBJECTIVE: To evaluate a new system, ISAID (Internet-based Semi-automated Indexing of Documents), and to generate textbook indexes that are more detailed and more useful to readers.
DESIGN: Pilot evaluation: simple, nonrandomized trial comparing ISAID with manual indexing methods. Methods evaluation: randomized, cross-over trial comparing three versions of ISAID and usability survey. PARTICIPANTS: Pilot evaluation: two physicians. Methods evaluation: twelve physicians, each of whom used three different versions of the system for a total of 36 indexing sessions. MEASUREMENTS: Total index term tuples generated per document per minute (TPM), with and without adjustment for concordance with other subjects; inter-indexer consistency; ratings of the usability of the ISAID indexing system.
RESULTS: Compared with manual methods, ISAID decreased indexing times greatly. Using three versions of ISAID, inter-indexer consistency ranged from 15% to 65% with a mean of 41%, 31%, and 40% for each of three documents. Subjects using the full version of ISAID were faster (average TPM: 5.6) and had higher rates of concordant index generation. There were substantial learning effects, despite our use of a training/run-in phase. Subjects using the full version of ISAID were much faster by the third indexing session (average TPM: 9.1). There was a statistically significant increase in three-subject concordant indexing rate using the full version of ISAID during the second indexing session (p < 0.05).
SUMMARY: Users of the ISAID indexing system create complex, precise, and accurate indexing for full-text documents much faster than users of manual methods. Furthermore, the natural language processing methods that ISAID uses to suggest indexes contributes substantially to increased indexing speed and accuracy.

Entities:  

Mesh:

Year:  2002        PMID: 12386114      PMCID: PMC349380          DOI: 10.1197/jamia.m1075

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  20 in total

1.  Knowledge requirements for automated inference of medical textbook markup.

Authors:  D C Berrios; A Kehler; L M Fagan
Journal:  Proc AMIA Symp       Date:  1999

2.  Metaphrase: an aid to the clinical conceptualization and formalization of patient problems in healthcare enterprises.

Authors:  M S Tuttle; N E Olson; K D Keck; W G Cole; M S Erlbaum; D D Sherertz; C G Chute; P L Elkin; G E Atkin; B H Kaihoi; C Safran; D Rind; V Law
Journal:  Methods Inf Med       Date:  1998-11       Impact factor: 2.176

3.  Answering clinical questions.

Authors:  M L Chambliss; J Conley
Journal:  J Fam Pract       Date:  1996-08       Impact factor: 0.493

4.  Dynamic organization of search results using the UMLS.

Authors:  W Pratt
Journal:  Proc AMIA Annu Fall Symp       Date:  1997

5.  Identification of findings suspicious for breast cancer based on natural language processing of mammogram reports.

Authors:  N L Jain; C Friedman
Journal:  Proc AMIA Annu Fall Symp       Date:  1997

6.  Extracting findings from narrative reports: software transferability and sources of physician disagreement.

Authors:  G Hripcsak; G J Kuperman; C Friedman
Journal:  Methods Inf Med       Date:  1998-01       Impact factor: 2.176

7.  Generic queries for meeting clinical information needs.

Authors:  J J Cimino; A Aguirre; S B Johnson; P Peng
Journal:  Bull Med Libr Assoc       Date:  1993-04

8.  Contextual models of clinical publications for enhancing retrieval from full-text databases.

Authors:  G P Purcell; E H Shortliffe
Journal:  Proc Annu Symp Comput Appl Med Care       Date:  1995

9.  Analysis of questions asked by family doctors regarding patient care.

Authors:  J W Ely; J A Osheroff; M H Ebell; G R Bergus; B T Levy; M L Chambliss; E R Evans
Journal:  BMJ       Date:  1999-08-07

10.  Identification of suspected tuberculosis patients based on natural language processing of chest radiograph reports.

Authors:  N L Jain; C A Knirsch; C Friedman; G Hripcsak
Journal:  Proc AMIA Annu Fall Symp       Date:  1996
View more
  8 in total

1.  A pilot study of contextual UMLS indexing to improve the precision of concept-based representation in XML-structured clinical radiology reports.

Authors:  Yang Huang; Henry J Lowe; William R Hersh
Journal:  J Am Med Inform Assoc       Date:  2003-08-04       Impact factor: 4.497

2.  Improved identification of noun phrases in clinical radiology reports using a high-performance statistical natural language parser augmented with the UMLS specialist lexicon.

Authors:  Yang Huang; Henry J Lowe; Dan Klein; Russell J Cucina
Journal:  J Am Med Inform Assoc       Date:  2005-01-31       Impact factor: 4.497

3.  Constructing a concise medical taxonomy.

Authors:  Bruce McGregor
Journal:  J Med Libr Assoc       Date:  2005-01

4.  Comparison of vector space model methodologies to reconcile cross-species neuroanatomical concepts.

Authors:  P R Srinivas; Shang-Heng Wei; Nello Cristianini; E G Jones; F A Gorin
Journal:  Neuroinformatics       Date:  2005

5.  Modeling the relationship between search terms in clinical queries.

Authors:  Roni F Zeiger; Christopher D Stave; Florian Schmitzberger; Lawrence M Fagan
Journal:  AMIA Annu Symp Proc       Date:  2005

6.  Clinical Digital Libraries Project: design approach and exploratory assessment of timely use in clinical environments.

Authors:  Steven L Maccall
Journal:  J Med Libr Assoc       Date:  2006-04

7.  EliXR: an approach to eligibility criteria extraction and representation.

Authors:  Chunhua Weng; Xiaoying Wu; Zhihui Luo; Mary Regina Boland; Dimitri Theodoratos; Stephen B Johnson
Journal:  J Am Med Inform Assoc       Date:  2011-07-31       Impact factor: 4.497

8.  Improving precision in concept normalization.

Authors:  Mayla Boguslav; K Bretonnel Cohen; William A Baumgartner; Lawrence E Hunter
Journal:  Pac Symp Biocomput       Date:  2018
  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.