Proceedings of the 19th SIGBioMed Workshop on Biomedical Language Processing, 2020.

Demner-Fushman D, Cohen KB, Ananiadou S, Tsujii J

Journal of the American Medical Informatics Association, 2020: 27 (2), 194-201.


The past year has been more than exciting for natural language processing in general, and for biomedical natural language processing in particular. A gradual accretion of studies of reproducibility and replicability in natural language processing, biomedical and otherwise had been making it clear that the reproducibility crisis that has hit most of the rest of science is not going to spare text mining or its related fields. Then, in March of 2020, much of the world ground to a sudden halt. The outbreak of the COVID-19 disease caused by the novel coronavirus SARS-CoV-2 made computational work more obviously relevant than it had perhaps ever been before. Suddenly, newscasters were arguing about viral clades, the daily news was full of stories about modelling, and your neighbor had heard of PCR. But, some of us did not really see a role for natural language processing in the brave new world of computational instant reactions to an international pandemic. That was wrong. In mid-late March of 2020, a joint project between the Allen Artificial Intelligence Institute (Ai2), the National Library of Medicine (NLM), and the White House Office of Science and Technology Policy (OSTP) released CORD-19, a corpus of work on the SARS-CoV-2 virus, on COVID-19 disease, and on related coronavirus research. It was immediately notable for its inclusion of "gray literature" from preprint servers, which mostly have been neglected in text mining research, as well as for its flexibility with regards to licensing of content types. Perhaps most importantly, it was released in conjunction with a number of task types, including one related to ethics–although the value of medical ethics has been widely obvious since the Nazi "medical" experimentation horrors of the Second World War, the worldwide pandemic has made the value of medical ethicists more apparent to the general public than at any time since. Those task type definitions enabled the broader natural language processing community to jump into the fray quite quickly, and initial results have been quick to arrive. Meanwhile, the pandemic did nothing to slow research in biomedical natural language processing on any other topic, either. That can be seen in the fact that this year the Association for Computational Linguistics SIGBIOMED workshop on biomedical natural language processing received 73 submissions. The unfortunate effect of the pandemic was the cancellation of the physical workshop, which would have allowed acceptance of all high-quality submissions as posters, if not for podium presentations. Indeed, the poster sessions at BioNLP have been continuously growing in size, due to the large number of high-quality submissions that the workshop receives annually. Unfortunately, because this year the Association for Computational Linguistics annual meeting will take place online only, there will be no poster session for the workshop. Consequently, only a handful of submissions could be accepted for presentation. Transitioning of the traditional conferences to online presentations at the beginning of the COVID-19 pandemic showed that the traditional presentation formats are not as engaging remotely as they are in the context of in-person sessions. We are therefore exploring a new form of presentation, hoping it will be more engaging, interactive, and informative: 22 papers (about 30% of the submissions) will be presented in panel-like sessions. Papers will be grouped by similarity of topic, meaning that participants with related interests will be able to interact regarding their papers with a hopefully optimal number of people on line at the same time. As we write this introduction, the conference plans and platform are still evolving, as are the daily lives of much of the planet, so we hope that you will join us in planning for the worst, while hoping for the best.

Demner-Fushman D, Cohen KB, Ananiadou S, Tsujii J. Proceedings of the 19th SIGBioMed Workshop on Biomedical Language Processing, 2020. 
Journal of the American Medical Informatics Association, 2020: 27 (2), 194-201.