BioNLP 2023
BIONLP 2023 and Shared Tasks @ ACL 2023
The 22nd BioNLP workshop associated with the ACL SIGBIOMED special interest group is co-located with ACL 2023
IMPORTANT DATES
Coming Soon
WORKSHOP OVERVIEW AND SCOPE
The BioNLP workshop associated with the ACL SIGBIOMED special interest group has established itself as the primary venue for presenting foundational research in language processing for the biological and medical domains. The workshop is running every year since 2002 and continues getting stronger. BioNLP welcomes and encourages work on languages other than English, and inclusion and diversity. BioNLP truly encompasses the breadth of the domain and brings together researchers in bio- and clinical NLP from all over the world. The workshop will continue presenting work on a broad and interesting range of topics in NLP. The interest to biomedical language has broadened significantly due to the COVID-19 pandemic and continues to grow: as access to information becomes easier and more people generate and access health-related text, it becomes clearer that only language technologies can enable and support adequate use of the biomedical text.
BioNLP 2023 will be particularly interested in language processing that supports DEIA (Diversity, Equity, Inclusion and Accessibility). The work on detection and mitigation of bias and misinformation continues to be of interest. Research in languages other than English, particularly, under-represented languages, and health disparities are always of interest to BioNLP.
Other active areas of research include, but are not limited to:
- Tangible results of biomedical language processing applications;
- Entity identification and normalization (linking) for a broad range of semantic categories;
- Extraction of complex relations and events;
- Discourse analysis;
- Anaphora/coreference resolution;
- Text mining / Literature based discovery;
- Summarization;
- Τext simplification;
- Question Answering;
- Resources and strategies for system testing and evaluation;
- Infrastructures and pre-trained language models for biomedical NLP (Processing and annotation platforms);
- Development of synthetic data & data augmentation;
- Translating NLP research into practice;
- Getting reproducible results.
Program Committee
* Sophia Ananiadou, National Centre for Text Mining and University of Manchester, UK * Saadullah Amin, Saarland University, Germany * Emilia Apostolova, Anthem, Inc., USA * Eiji Aramaki, University of Tokyo, Japan * Timothy Baldwin, University of Melbourne, Australia * Spandana Balumuri, National Institute of Technology Karnataka, India * Steven Bethard, University of Arizona, USA * Robert Bossy, Inrae, Université Paris Saclay, France * Berry de Bruijn, National Research Council Canada * Leonardo Campillos-Llanos, Centro Superior de Investigaciones Científicas - CSIC, Spain * Kevin Bretonnel Cohen, University of Colorado School of Medicine, USA * Fenia Christopoulou, Huawei Noah's Ark lab, UK * Brian Connolly, Ohio, USA * Mike Conway, University of Utah, USA * Manirupa Das, Amazon, USA * Surabhi Datta, The University of Texas Health Science Center at Houston, USA * Dina Demner-Fushman, US National Library of Medicine * Dmitriy Dligach, Loyola University Chicago, USA * Kathleen C. Fraser, National Research Council Canada * Travis Goodwin, US National Library of Medicine * Natalia Grabar, CNRS, U Lille, France * Cyril Grouin, LIMSI - CNRS, France * Tudor Groza, EMBL-EBI * Deepak Gupta, US National Library of Medicine * Sam Henry, Christopher Newport University, USA * William Hogan, UCSD, USA * Kexin Huang, Stanford University, USA * Brian Hur, University of Melbourne, Australia * Richard Jackson, AstraZeneca * Antonio Jimeno Yepes, IBM, Melbourne Area, Australia * Sarvnaz Karimi, CSIRO, Australia * Nazmul Kazi, Montana State University, USA * Won Gyu KIM, US National Library of Medicine * Ari Klein, University of Pennsylvania, USA * Roman Klinger, University of Stuttgart, Germany * Andre Lamurias, Aalborg University, DK * Majid Latifi, National College of Ireland * Alberto Lavelli, FBK-ICT, Italy * Robert Leaman, US National Library of Medicine * Lung-Hao Lee, National Central University, Taiwan * Ulf Leser, Humboldt-Universität zu Berlin, Germany * Diwakar Mahajan, IBM Thomas J. Watson Research Center, USA * Mark-Christoph Müller, Heidelberg Institute for Theoretical Studies, Germany * Claire Nédellec, INRA, Université Paris-Saclay, FR * Guenter Neumann, DFKI, Saarland, Germany * Aurelie Neveol, LIMSI - CNRS, France * Mariana Neves, Hasso-Plattner-Institute at the University of Potsdam, Germany * Yifan Peng, Weill Cornell Medical College, USA * Francisco J. Ribadas-Pena, Universidade de Vigo, Spain * Anthony Rios, The University of Texas at San Antonio, USA * Angus Roberts, King's College London, UK * Kirk Roberts, The University of Texas Health Science Center at Houston, USA * Roland Roller, DFKI, Germany * Mourad Sarrouti, Sumitovant Biopharma, Inc., USA * Mario Sänger, Humboldt-Universität zu Berlin, Germany * Diana Sousa, Universidade de Lisboa, Portugal * Michael Spranger, Sony, Tokyo, Japan * Peng Su, University of Delaware, USA * Madhumita Sushil, University of California, San Francisco, USA * Karin Verspoor, RMIT University, Melbourne, Australia * Roger Wattenhofer, ETH Zurich, Switzerland * Leon Weber, Humboldt Universität Berlin, Germany * Nathan M. White, James Cook University, Australia * Davy Weissenbacher, University of Pennsylvania, USA * W John Wilbur, US National Library of Medicine * Amelie Wührl, University of Stuttgart, Germany * Dongfang Xu, Harvard University, USA * Shweta Yadav, University of Illinois Chicago, USA * Jingqing Zhang, Imperial College London, UK * Ayah Zirikly, Johns Hopkins University, USA * Pierre Zweigenbaum, LIMSI - CNRS, France
SHARED TASK: MedVidQA 2022
The first challenge on Medical Video Question Answering is collocated with the BioNLP 2022 Workshop. MedVidQA focuses on providing relevant segments of videos as answers to health-related questions. Medical videos may provide the best possible answers to many first aid, medical emergency, and medical education questions. Please check the challenge website for details on the tasks, datasets, and submission guidelines: https://medvidqa.github.io
Organizers
Dina Demner-Fushman, US National Library of Medicine Kevin Bretonnel Cohen, University of Colorado School of Medicine Sophia Ananiadou, National Centre for Text Mining and University of Manchester, UK Jun-ichi Tsujii, National Institute of Advanced Industrial Science and Technology, Japan
Dual submission policy
Papers may NOT be submitted to the BioNLP 2022 workshop if they are or will be concurrently submitted to another meeting or publication.