PUB - Publikationen an der Universität Bielefeld

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/.