Some items of possible interest to bilbiometricians

[Eugene Garfield]

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TITLE:          Bibliographical Analysis: A Historical Introduction, by
                G.T. Tanselle (Book Review, English)
AUTHOR:         Richardson, B
SOURCE:         MODERN LANGUAGE REVIEW 105 (Pt 4). OCT 2010. p.1132-1133
                MANEY PUBLISHING, LEEDS

SEARCH TERM(S):  BIBLIOGRAPHIC*  item_title


AUTHOR ADDRESS: B Richardson, Univ Leeds, Leeds LS2 9JT, W Yorkshire,
                England

 
TITLE:          Documentation: A History and Critique of Attribution,
                Commentary, Glosses, Marginalia, Notes, Bibliographies,
Works-Cited
                Lists, and Citation Indexing and Analysis, by R.
Hauptman (Book Review,
                English)
AUTHOR:         Ritter, RM
SOURCE:         MODERN LANGUAGE REVIEW 105 (Pt 4). OCT 2010. p.1133-1135
                MANEY PUBLISHING, LEEDS

SEARCH TERM(S):  CITED  item_title; CITATION  item_title;
                 CITATION*  item_title


AUTHOR ADDRESS: RM Ritter, Univ Oxford, Oxford OX1 2JD, England

 
TITLE:          The future of philosophical journals in a European
                scientific landscape (Editorial Material, German)
SOURCE:         PHILOSOPHISCHE RUNDSCHAU 57 (3). 2010. p.205-206 J C B
                MOHR, TUBINGEN

SEARCH TERM(S):  JOURNALS  item_title; EDITORIAL  doctype


 
TITLE:          Unplanned redundant publication. A consequence of too
                many cardiovascular journals? (Letter, English)
AUTHOR:         Heras, M; Avanzas, P; Bayes-Genis, A; Pan, M; de Isla,
                LP; Sanchis, J
SOURCE:         HEART 96 (21). NOV 2010. p.1780 B M J PUBLISHING GROUP,
                LONDON

SEARCH TERM(S):  JOURNALS  item_title; LETTER*  doctype


AUTHOR ADDRESS: M Heras, Revista Espanola Cardiol, Ntra Sra Guadalupe
5-7,
                Madrid 28028, Spain

 
TITLE:          Unplanned redundant publication. A consequence of too
                many cardiovascular journals? Reply (Letter, English)
AUTHOR:         Timmis, A
SOURCE:         HEART 96 (21). NOV 2010. p.1780 B M J PUBLISHING GROUP,
                LONDON

SEARCH TERM(S):  JOURNALS  item_title; LETTER*  doctype


AUTHOR ADDRESS: A Timmis, London Chest Hosp, Dept Cardiol, Bonner Rd,
                London E2 9JX, England

 
 
 
 
 
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TITLE:          ExaCT: automatic extraction of clinical trial
                characteristics from journal publications (Article,
English)
AUTHOR:         Kiritchenko, S; de Bruijn, B; Carini, S; Martin, J; Sim,
                I
SOURCE:         BMC MEDICAL INFORMATICS AND DECISION MAKING 10. SEP 28
                2010. p.NIL_1-NIL_17 BIOMED CENTRAL LTD, LONDON

SEARCH TERM(S):  JOURNAL  item_title

KEYWORDS+:       RANDOMIZED CONTROLLED-TRIALS; CONSORT STATEMENT;
                BIOMEDICAL TEXT; ABSTRACTS; ARTICLES

ABSTRACT:       Background: Clinical trials are one of the most
important
sources of evidence for guiding evidence-based practice and the design
of
new trials. However, most of this information is available only in free
text e.g., in journal publications - which is labour intensive to
process
for systematic reviews, meta-analyses, and other evidence synthesis
studies. This paper presents an automatic information extraction system,
called ExaCT, that assists users with locating and extracting key trial
characteristics (e.g., eligibility criteria, sample size, drug dosage,
primary outcomes) from full-text journal articles reporting on
randomized
controlled trials (RCTs).

Methods: ExaCT consists of two parts: an information extraction (IE)
engine that searches the article for text fragments that best describe
the trial characteristics, and a web browser-based user interface that
allows human reviewers to assess and modify the suggested selections.
The
IE engine uses a statistical text classifier to locate those sentences
that have the highest probability of describing a trial characteristic.
Then, the IE engine's second stage applies simple rules to these
sentences to extract text fragments containing the target answer. The
same approach is used for all 21 trial characteristics selected for this
study.

Results: We evaluated ExaCT using 50 previously unseen articles
describing RCTs. The text classifier (first stage) was able to recover
88% of relevant sentences among its top five candidates (top5 recall)
with the topmost candidate being relevant in 80% of cases (top1
precision). Precision and recall of the extraction rules (second stage)
were 93% and 91%, respectively. Together, the two stages of the
extraction engine were able to provide (partially) correct solutions in
992 out of 1050 test tasks (94%), with a majority of these (696)
representing fully correct and complete answers.

Conclusions: Our experiments confirmed the applicability and efficacy of
ExaCT. Furthermore, they demonstrated that combining a statistical
method
with 'weak' extraction rules can identify a variety of study
characteristics. The system is flexible and can be extended to handle
other characteristics and document types (e.g., study protocols).

AUTHOR ADDRESS: S Kiritchenko, CNR, Inst Informat Technol, Ottawa, ON,
                Canada