TY  - JOUR
AB  - Translational neuroscience in the field of spinal
cord injuries (SCI) faces a strong disproportion
between immense preclinical research efforts
and a lack of therapeutic approaches success-
ful in human patients: Currently, preclinical
research on SCI yields more than 3,000 new
publications per year (8,000 when including
the whole central nervous system, growing at
an exponential rate), whereas none of the result-
ing therapeutic concepts has led to functional
recovery of neural tissue in humans. Improving
clinical researchers’ information access there-
fore carries the potential to support more effec-
tive selection of promising therapy candidates
from preclinical studies. Thus, automated in-
formation extraction from scientific publica-
tions contributes to enabling meta studies and
therapy grading by aggregating relevant infor-
mation from the entire body of previous work
on SCI.
We present SCIE, an automated information
extraction pipeline capable of detecting rele-
vant information in SCI publications based on
ontological entity and probabilistic relation de-
tection. The input are plain text or PDF doc-
uments. As output, the user choses between
an online visualization or a machine-readable
format. Compared to human gold standard
annotations, our system achieves an average
extraction performance of 76 % precision and
52 % recall (F1-measure 0.59).
An instance of the webservice is available at
http://scie.sc.cit-ec.uni-bielefeld.de/. SCIE is
free software licensed under the AGPL and can
be downloaded for local installation at http:
//opensource.cit-ec.de/projects/scie/.
DA  - 2015
DO  - 10.1101/013458
KW  - web service
KW  - pre-clinical studies
KW  - translational neurobiology
KW  - spinal cord injury
KW  - text mining
KW  - information extraction
LA  - eng
PY  - 2015
TI  - SCIE: Information Extraction for Spinal Cord Injury Preclinical Experiments – A Webservice and Open Source Toolkit
UR  - https://nbn-resolving.org/urn:nbn:de:0070-pub-27121074
Y2  - 2024-11-21T22:42:19
ER  -