Proceedings of BioNLP 2014

Abstract

IntroductionThe first day of the BioNLP 2014 workshop continues following the course set by the first ACL workshop on Natural Language Processing in the Biomedical Domain that was held in 2002: BioNLP 2014 provides a venue for exploring challenges and techniques in processing biomedical language and brings together researchers from computational linguistics and biomedical informatics. The submissions to the first day of 2014 workshop organized by SIGBioMed were traditionally very strong and continued demonstrating the considerable breadth of research in biomedical language processing. The 2014 workshop has accepted 12 full and short papers for oral presentations and 7 posters. The first day of the workshop features a keynote that expands the scope of BioNLP beyond its already remarkable breadth The second day of the workshop features a paper submitted to the special track on NLP approaches for assessment of clinical conditions. Kathleen C. Fraser presents the featured talk on using statistical parsing to detect agrammatic aphasia. The track organizers, Thamar Solorio and Yang Liu, serve as discussants.The second day further features an exciting panel that brings together organizers of several shared tasks in biomedical information retrieval and natural language processing. The panel introduces the workshop participants to the long-standing and relatively new community-wide challenges in biomedical and clinical language processing. It also provides an opportunity to discuss the future of the shared tasks in this domain. AcknowledgmentsAs always, we are profoundly grateful to the authors who chose BioNLP as venue for presenting their innovative research. The authors' willingness to share their work through BioNLP consistently makes the workshop noteworthy among the increasing numbers of available venues. We are equally indebted to the program committee members (listed elsewhere in this volume) who produced at least three thorough reviews per paper on a tight review schedule and with an admirable level of insight.iii AbstractZoonotic viruses, viruses that are transmittable between animals and humans, represent emerging or re-emerging pathogens that pose significant public health threats throughout the world. It is therefore crucial to advance current surveillance mechanisms for these viruses through outlets such as phylogeography. Phylogeographic techniques may be applied to trace the origins and geographical distribution of these viruses using sequence and location data, which are often obtained from publicly available databases such as GenBank. Despite the abundance of zoonotic viral sequence data in GenBank records, phylogeographic analysis of these viruses is greatly limited by the lack of adequate geographic metadata. Although more detailed information may often be found in the related articles referenced in these records, manual extraction of this information presents a severe bottleneck. In this work, we propose an automated system for extracting this information using Natural Language Processing (NLP)...