Since our last renewal, the challenges for biomedical researchers of keeping up with the scientific literature have become even more acute. Last year marked the first time that Medline indexed more than a million journal articles; more than 210,000 of these had full text deposited in PubMedCentral, bringing the total number of full texts archived in PMC to over 3 million. The stunning pleiotropy of genes and their products, combined with the adoption of genome-scale technologies throughout biomedical research, has made obsolete the notion that reading within one's own specialty plus a few top journals is enough to keep track of all of the results relevan to one's research. Fortunately, advances in biomedical natural language processing and increasing access to digital full text journal publications offer the potential for innovative new approaches to delivering relevant information to working bench scientists. We hypothesize that realizing the potential of biomedical natural language processing applied to full text journal articles to make a sustained and powerful contribution to biomedical research requires contextualizing Biomedical natural language processing in the daily life of bench scientists, focusing on their unmet information gathering needs, and providing interfaces that fit well into existing research workflows.
This project will affect public health by increasing the ability of biologists to investigate hypotheses using the biomedical literature. Realizing the potential of biomedical natural language processing applied to full text journal articles to make a sustained and powerful contribution to biomedical research requires contextualizing biomedical natural language processing in the daily life of bench scientists, focusing on their unmet information gathering needs, and providing interfaces that fit well into existing research workflows.
|Boguslav, Mayla; Cohen, K Bretonnel; Baumgartner, William A et al. (2018) Improving precision in concept normalization. Pac Symp Biocomput 23:566-577|
|Cohen, K Bretonnel; Xia, Jingbo; Zweigenbaum, Pierre et al. (2018) Three Dimensions of Reproducibility in Natural Language Processing. LREC Int Conf Lang Resour Eval 2018:156-165|
|Callahan, Tiffany J; Baumgartner, William A; Bada, Michael et al. (2018) OWL-NETS: Transforming OWL Representations for Improved Network Inference. Pac Symp Biocomput 23:133-144|
|Cohen, K Bretonnel; Lanfranchi, Arrick; Choi, Miji Joo-Young et al. (2017) Coreference annotation and resolution in the Colorado Richly Annotated Full Text (CRAFT) corpus of biomedical journal articles. BMC Bioinformatics 18:372|
|Kao, David P; Stevens, Laura M; Hinterberg, Michael A et al. (2017) Phenotype-Specific Association of Single-Nucleotide Polymorphisms with Heart Failure and Preserved Ejection Fraction: a Genome-Wide Association Analysis of the Cardiovascular Health Study. J Cardiovasc Transl Res 10:285-294|
|Hooper, Joan E; Feng, Weiguo; Li, Hong et al. (2017) Systems biology of facial development: contributions of ectoderm and mesenchyme. Dev Biol 426:97-114|
|Cohen, K Bretonnel; Fort, Karën; Adda, Gilles et al. (2016) Ethical Issues in Corpus Linguistics And Annotation: Pay Per Hit Does Not Affect Effective Hourly Rate For Linguistic Resource Development On Amazon Mechanical Turk. LREC Int Conf Lang Resour Eval 2016:8-12|
|Cohen, K Bretonnel; Xia, Jingbo; Roeder, Christophe et al. (2016) Reproducibility in Natural Language Processing: A Case Study of Two R Libraries for Mining PubMed/MEDLINE. LREC Int Conf Lang Resour Eval 2016:6-12|
|Cohen, K Bretonnel; Baumgartner Jr, William A; Temnikova, Irina (2016) SuperCAT: The (New and Improved) Corpus Analysis Toolkit. LREC Int Conf Lang Resour Eval 2016:2784-2788|
|Eberlein, Jens; Davenport, Bennett; Nguyen, Tom et al. (2016) Aging promotes acquisition of naive-like CD8+ memory T cell traits and enhanced functionalities. J Clin Invest 126:3942-3960|
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