Difference between revisions of "BioNLP 2023"

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   * Yassine M'Rabet, US National Library of Medicine
 
   * Yassine M'Rabet, US National Library of Medicine
 
   * Aurelie Neveol, LIMSI - CNRS, France  
 
   * Aurelie Neveol, LIMSI - CNRS, France  
<!--  * Claire Nédellec, INRA, France -->
+
  * Claire Nédellec, INRA, France
 
   * Mariana Neves, German Federal Institute for Risk Assessment, Germany  
 
   * Mariana Neves, German Federal Institute for Risk Assessment, Germany  
 
   * Denis Newman-Griffis, Clinical Center, National Institutes of Health, USA
 
   * Denis Newman-Griffis, Clinical Center, National Institutes of Health, USA

Revision as of 13:59, 9 August 2019

SIGBIOMED

BIONLP 2019
Florence, Italy, Thursday, August 1, 2019

An ACL 2019 Workshop associated with the SIGBIOMED special interest group and featuring an associated task: MEDIQA 2019 ( https://sites.google.com/view/mediqa2019)


IMPORTANT DATES

  • Submission deadline: Friday May 10, 2019 11:59 PM Eastern US
  • Notification of acceptance: Friday, May 31, 2019
  • Camera-ready copy due from authors: Friday, June 7, 2019 -- Firm deadline due to ACL schedule.
  • Workshop: Thursday, August 1, 2019


BioNLP 2019 WORKSHOP PROGRAM

Thursday August 1, 2019
8:30–8:45Opening remarks
8:45–10:30Session 1: Clinical and Translational NLP
8:45–9:00Classifying the reported ability in clinical mobility descriptions
Denis Newman-Griffis, Ayah Zirikly, Guy Divita, Bart Desmet
9:00–9:15Learning from the Experience of Doctors: Automated Diagnosis of Appendicitis Based on Clinical Notes
Steven Kester Yuwono, Hwee Tou Ng, Kee Yuan Ngiam
9:15–9:30A Paraphrase Generation System for EHR Question Answering
Sarvesh Soni and Kirk Roberts
9:30–9:45REflex: Flexible Framework for Relation Extraction in Multiple Domains
Geeticka Chauhan, Matthew McDermott, Peter Szolovits
9:45–10:00Analysing Representations of Memory Impairment in a Clinical Notes Classification Model
Mark Ormerod, Jesús Martínez-del-Rincón, Neil Robertson, Bernadette McGuinness, Barry Devereux
10:00–10:15Transfer Learning in Biomedical Natural Language Processing: An Evaluation of BERT and ELMo on Ten Benchmarking Datasets
Yifan Peng, Shankai Yan, Zhiyong Lu
10:15–10:30Combining Structured and Free-text Electronic Medical Record Data for Real-time Clinical Decision Support
Emilia Apostolova, Tony Wang, Tim Tschampel, Ioannis Koutroulis, Tom Velez
10:30–11:00Coffee Break
11:00–12:00Poster Session
 MoNERo: a Biomedical Gold Standard Corpus for the Romanian Language
Maria Mitrofan, Verginica Barbu Mititelu, Grigorina Mitrofan
 Domain Adaptation of SRL Systems for Biological Processes
Dheeraj Rajagopal, Nidhi Vyas, Aditya Siddhant, Anirudha Rayasam, Niket Tandon, Eduard Hovy
 Deep Contextualized Biomedical Abbreviation Expansion
Qiao Jin, Jinling Liu, Xinghua Lu
 RNN Embeddings for Identifying Difficult to Understand Medical Words
Hanna Pylieva, Artem Chernodub, Natalia Grabar, Thierry Hamon
 A distantly supervised dataset for automated data extraction from diagnostic studies
Christopher Norman, Mariska Leeflang, René Spijker, Evangelos Kanoulas, Aurélie Névéol
 Query selection methods for automated corpora construction with a use case in food-drug interactions
Georgeta Bordea, Tsanta Randriatsitohaina, Fleur Mougin, Natalia Grabar, Thierry Hamon
 Enhancing biomedical word embeddings by retrofitting to verb clusters
Billy Chiu, Simon Baker, Martha Palmer, Anna Korhonen
 A Comparison of Word-based and Context-based Representations for Classification Problems in Health Informatics
Aditya Joshi, Sarvnaz Karimi, Ross Sparks, Cecile Paris, C Raina MacIntyre
 Constructing large scale biomedical knowledge bases from scratch with rapid annotation of interpretable patterns
Julien Fauqueur, Ashok Thillaisundaram, Theodosia Togia
 First Steps towards Building a Medical Lexicon for Spanish with Linguistic and Semantic Information
Leonardo Campillos-Llanos
 Incorporating Figure Captions and Descriptive Text in MeSH Term Indexing
Xindi Wang and Robert E. Mercer
 BioRelEx 1.0: Biological Relation Extraction Benchmark
Hrant Khachatrian, Lilit Nersisyan, Karen Hambardzumyan, Tigran Galstyan, Anna Hakobyan, Arsen Arakelyan, Andrey Rzhetsky, Aram Galstyan
 Extraction of Lactation Frames from Drug Labels and LactMed
Heath Goodrum, Meghana Gudala, Ankita Misra, Kirk Roberts
 Annotating Temporal Information in Clinical Notes for Timeline Reconstruction: Towards the Definition of Calendar Expressions
Natalia Viani, Hegler Tissot, Ariane Bernardino, Sumithra Velupillai
 Leveraging Sublanguage Features for the Semantic Categorization of Clinical Terms
Leonie Grön, Ann Bertels, Kris Heylen
 Enhancing PIO Element Detection in Medical Text Using Contextualized Embedding
Hichem Mezaoui, Isuru Gunasekara, Aleksandr Gontcharov
 Contributions to Clinical Named Entity Recognition in Portuguese
Fábio Lopes, César Teixeira, Hugo Gonçalo Oliveira
 Can Character Embeddings Improve Cause-of-Death Classification for Verbal Autopsy Narratives?
Zhaodong Yan, Serena Jeblee, Graeme Hirst
 Is artificial data useful for biomedical Natural Language Processing algorithms?
Zixu Wang, Julia Ive, Sumithra Velupillai, Lucia Specia
 ChiMed: A Chinese Medical Corpus for Question Answering
Yuanhe Tian, Weicheng Ma, Fei Xia, Yan Song
 Clinical Concept Extraction for Document-Level Coding
Sarah Wiegreffe, Edward Choi, Sherry Yan, Jimeng Sun, Jacob Eisenstein
 Clinical Case Reports for NLP
Cyril Grouin, Natalia Grabar, Vincent Claveau, Thierry Hamon
 Two-stage Federated Phenotyping and Patient Representation Learning
Dianbo Liu, Dmitriy Dligach, Timothy Miller
 Transfer Learning for Causal Sentence Detection
Manolis Kyriakakis, Ion Androutsopoulos, Artur Saudabayev, Joan Ginés i Ametllé
12:00–12:30Session 2: Ontology and Typology
12:00–12:15Embedding Biomedical Ontologies by Jointly Encoding Network Structure and Textual Node Descriptors
Sotiris Kotitsas, Dimitris Pappas, Ion Androutsopoulos, Ryan McDonald, Marianna Apidianaki
12:15–12:30Simplification-induced transformations: typology and some characteristics
Anaïs Koptient, Rémi Cardon, Natalia Grabar
12:30–14:00Lunch break
14:00–15:30Session 3: Literature mining approaches and models
14:00–14:15ScispaCy: Fast and Robust Models for Biomedical Natural Language Processing
Mark Neumann, Daniel King, Iz Beltagy, Waleed Ammar
14:15–14:30Improving Chemical Named Entity Recognition in Patents with Contextualized Word Embeddings
Zenan Zhai, Dat Quoc Nguyen, Saber Akhondi, Camilo Thorne, Christian Druckenbrodt, Trevor Cohn, Michelle Gregory, Karin Verspoor
14:30–14:45Improving classification of Adverse Drug Reactions through Using Sentiment Analysis and Transfer Learning
Hassan Alhuzali and Sophia Ananiadou
14:45–15:00Exploring Diachronic Changes of Biomedical Knowledge using Distributed Concept Representations
Gaurav Vashisth, Jan-Niklas Voigt-Antons, Michael Mikhailov, Roland Roller
15:00–15:15Extracting relations between outcomes and significance levels in Randomized Controlled Trials (RCTs) publications
Anna Koroleva and Patrick Paroubek
15:30–16:00Coffee Break
16:00–17:00Session 4: Shared Task
16:00–16:15Overview of the MEDIQA 2019 Shared Task on Textual Inference, Question Entailment and Question Answering
Asma Ben Abacha, Chaitanya Shivade and Dina Demner-Fushman
16:15–16:30PANLP at MEDIQA 2019: Pre-trained Language Models, Transfer Learning and Knowledge Distillation
Wei Zhu, Xiaofeng Zhou, Keqiang Wang, Xun Luo, Xiepeng Li, Yuan Ni and Guotong Xie
16:30–16:45Pentagon at MEDIQA 2019: Multi-task Learning for Filtering and Re-ranking Answers using Language Inference and Question Entailment
Hemant Pugaliya, Karan Saxena, Shefali Garg, Sheetal Shalini, Prashant Gupta, Eric Nyberg and Teruko Mitamura
16:45–17:00DoubleTransfer at MEDIQA 2019: Multi-Source Transfer Learning for Natural Language Understanding in the Medical Domain
Yichong Xu, Xiaodong Liu, Chunyuan Li, Hoifung Poon and Jianfeng Gao
17:00–18:00Shared Task Poster Session
 Surf at MEDIQA 2019: Improving Performance of Natural Language Inference in the Clinical Domain by Adopting Pre-trained Language Model
Jiin Nam, Seunghyun Yoon and Kyomin Jung
 WTMED at MEDIQA 2019: A Hybrid Approach to Biomedical Natural Language Inference
Zhaofeng Wu, Yan Song, Sicong Huang, Yuanhe Tian and Fei Xia
 KU_ai at MEDIQA 2019: Domain-specific Pre-training and Transfer Learning for Medical NLI
Cemil Cengiz, Ulaş Sert and Deniz Yuret
 DUT-NLP at MEDIQA 2019: An Adversarial Multi-Task Network to Jointly Model Recognizing Question Entailment and Question Answering
Huiwei Zhou, Xuefei Li, Weihong Yao, Chengkun Lang and Shixian Ning
 DUT-BIM at MEDIQA 2019: Utilizing Transformer Network and Medical Domain-Specific Contextualized Representations for Question Answering
Huiwei Zhou, Bizun Lei, Zhe Liu and Zhuang Liu
 Dr.Quad at MEDIQA 2019: Towards Textual Inference and Question Entailment using contextualized representations
Vinayshekhar Bannihatti Kumar, Ashwin Srinivasan, Aditi Chaudhary, James Route, Teruko Mitamura and Eric Nyberg
 Sieg at MEDIQA 2019: Multi-task Neural Ensemble for Biomedical Inference and Entailment
Sai Abishek Bhaskar, Rashi Rungta, James Route, Eric Nyberg and Teruko Mitamura
 IIT-KGP at MEDIQA 2019: Recognizing Question Entailment using Sci-BERT stacked with a Gradient Boosting Classifier
Prakhar Sharma and Sumegh Roychowdhury
 ANU-CSIRO at MEDIQA 2019: Question Answering Using Deep Contextual Knowledge
Vincent Nguyen, Sarvnaz Karimi and Zhenchang Xing
 MSIT_SRIB at MEDIQA 2019: Knowledge Directed Multi-task Framework for Natural Language Inference in Clinical Domain.
Sahil Chopra, Ankita Gupta and Anupama Kaushik
 UU_TAILS at MEDIQA 2019: Learning Textual Entailment in the Medical Domain
Noha Tawfik and Marco Spruit
 UW-BHI at MEDIQA 2019: An Analysis of Representation Methods for Medical Natural Language Inference
William Kearns, Wilson Lau and Jason Thomas
 Saama Research at MEDIQA 2019: Pre-trained BioBERT with Attention Visualisation for Medical Natural Language Inference
Kamal raj Kanakarajan, Suriyadeepan Ramamoorthy, Vaidheeswaran Archana, Soham Chatterjee and Malaikannan Sankarasubbu
 IITP at MEDIQA 2019: Systems Report for Natural Language Inference, Question Entailment and Question Answering
Dibyanayan Bandyopadhyay, Baban Gain, Tanik Saikh and Asif Ekbal
 LasigeBioTM at MEDIQA 2019: Biomedical Question Answering using Bidirectional Transformers and Named Entity Recognition
Andre Lamurias and Francisco M Couto
 NCUEE at MEDIQA 2019: Medical Text Inference Using Ensemble BERT-BiLSTM-Attention Model
Lung-Hao Lee, Yi Lu, Po-Han Chen, Po-Lei Lee and Kuo-Kai Shyu
 ARS_NITK at MEDIQA 2019:Analysing Various Methods for Natural Language Inference, Recognising Question Entailment and Medical Question Answering System
Anumeha Agrawal, Rosa Anil George, Selvan Suntiha Ravi, Sowmya Kamath and Anand Kumar

Program Committee

 * Hadi Amiri, Harvard Medical School, USA
 * Sophia Ananiadou, National Centre for Text Mining and University of Manchester, UK 
 * Emilia Apostolova, Language.ai, USA
 * Eiji Aramaki, University of Tokyo, Japan 
 * Asma Ben Abacha, US National Library of Medicine 
 * Cosmin (Adi) Bejan, Vanderbilt University, Nashville, TN 
 * Siamak Barzegar, Barcelona Supercomputing Center, Spain
 * Olivier Bodenreider, US National Library of Medicine 
 * Leonardo Campillos Llanos, Universidad Autónoma de Madrid, Spain
 * Qingyu Chen, US National Library of Medicine  
 * Fenia Christopoulou, National Centre for Text Mining and University of Manchester, UK 
 * Aaron Cohen, Oregon Health & Science University, USA 
 * Kevin Bretonnel Cohen, University of Colorado School of Medicine, USA 
 * Brian Connolly, Kroger Digital, USA 
 * Viviana Cotik, University of Buenos Aires, Argentina
 * Dina Demner-Fushman, US National Library of Medicine 
 * Travis Goodwin, The University of Texas at Dallas, USA
 * Natalia Grabar, CNRS, France 
 * Cyril Grouin, LIMSI - CNRS, France 
 * Tudor Groza, The Garvan Institute of Medical Research, Australia
 * Sadid Hasan, Philips Research, Cambridge, MA
 * Antonio Jimeno Yepes, IBM, Melbourne Area, Australia
 * Meizhi Ju, National Centre for Text Mining and University of Manchester, UK 
 * Will Kearns, University of Washington, USA
 * Halil Kilicoglu, US National Library of Medicine
 * Ari Klein, University of Pennsylvania, USA
 * Zfania Tom Korach, Harvard Medical School, USA
 * André Lamúrias, University of Lisbon, Portugal
 * Majid Latifi,  Trinity College Dublin, Ireland
 * Alberto Lavelli, FBK-ICT, Italy
 * Robert Leaman, US National Library of Medicine 
 * Ulf Leser, Humboldt-Universität zu Berlin, Germany 
 * Gal Levy-Fix, Columbia University, NY
 * Maolin Li, National Centre for Text Mining and University of Manchester, UK 
 * Ramon Maldonado, The University of Texas at Dallas, USA
 * Timothy Miller, Children’s Hospital Boston, USA 
 * Danielle L Mowery, VA Salt Lake City Health Care System, USA
 * Yassine M'Rabet, US National Library of Medicine
 * Aurelie Neveol, LIMSI - CNRS, France 
 * Claire Nédellec, INRA, France
 * Mariana Neves, German Federal Institute for Risk Assessment, Germany 
 * Denis Newman-Griffis, Clinical Center, National Institutes of Health, USA
 * Nhung Nguyen, The University of Manchester, UK
 * Karen O'Connor, University of Pennsylvania, USA
 * Yifan Peng, US National Library of Medicine 
 * Laura Plaza, UNED, Madrid, Spain
 * Sampo Pyysalo, University of Cambridge, UK 
 * Alastair Rae, US National Library of Medicine 
 * Francisco J. Ribadas-Pena, University of Vigo, Spain
 * Kirk Roberts, The University of Texas Health Science Center at Houston, USA 
 * Roland Roller, DFKI GmbH, Berlin, Germany
 * Sumegh Roychowdhury, Indian Institute of Technology Kharagpur
 * Max Savery, US National Library of Medicine 
 * Chaitanya Shivade, IBM Research, Almaden, USA
 * Diana Sousa, University of Lisbon, Portugal
 * Noha Seddik Tawfik, Arab Academy for Science and Technology, Egypt
 * Thy Thy Tran, National Centre for Text Mining and University of Manchester, UK 
 * Sumithra Velupillai, King’s College London, UK
 * Davy Weissenbacher, University of Pennsylvania, USA
 * W John Wilbur, US National Library of Medicine 
 * Shankai Yan, US National Library of Medicine 
 * Amir Yazdavar, Wright State University, USA
 * Chrysoula Zerva, National Centre for Text Mining and University of Manchester, UK 
 * Ayah Zirikly, Clinical Center, National Institutes of Health, USA
 * Seyedjamal Zolhavarieh, The University of Auckland, NZ
 * Pierre Zweigenbaum, LIMSI - CNRS, France

Organizers

 Kevin Bretonnel Cohen, University of Colorado School of Medicine
 Dina Demner-Fushman, US National Library 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 and University of Manchester, UK

WORKSHOP OVERVIEW AND SCOPE

The ACL BioNLP workshop associated with the 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 serves as both a venue for bringing together researchers in bio- and clinical NLP and exposing these researchers to the mainstream ACL research, and a venue for informing the mainstream ACL researchers about the fast growing and important domain. The workshop will continue presenting work on a broad and interesting range of topics in NLP.

The active areas of research include, but are not limited to:

  • Entity identification and normalization for a broad range of semantic categories
  • Extraction of complex relations and events
  • Semantic parsing
  • Discourse analysis
  • Anaphora /Coreference resolution
  • Text mining
  • Literature based discovery
  • Summarization
  • Question Answering
  • Resources and novel strategies for system testing and evaluation
  • Infrastructures for biomedical text mining
  • Processing and annotation platforms
  • Translating NLP research to practice
  • Research Reproducibility

SUBMISSION INSTRUCTIONS

Three types of submissions are invited: full papers, short papers and MEDIQA shared task participants' reports.

Full papers should not exceed eight (8) pages of text, plus unlimited references. Final versions of full papers will be given one additional page of content (up to 9 pages) so that reviewers' comments can be taken into account. Full papers are intended to be reports of original research. BioNLP aims to be the forum for interesting, innovative, and promising work involving biomedicine and language technology, whether or not yielding high performance at the moment. This by no means precludes our interest in and preference for mature results, strong performance, and thorough evaluation. Both types of research and combinations thereof are encouraged.

Short papers may consist of up to four (4) pages of content, plus unlimited references. Upon acceptance, short papers will still be given up to five (5) content pages in the proceedings. Appropriate short paper topics include preliminary results, application notes, descriptions of work in progress, etc.

MEDIQA shared task participants reports should conform to the long paper submission guidelines.

Electronic Submission

Submissions must be electronic and in PDF format, using the Softconf START conference management system at https://www.softconf.com/acl2019/bionlp/ We strongly recommend consulting the ACL Policies for Submission, Review, and Citation: https://www.aclweb.org/portal/content/new-policies-submission-review-and-citation and using ACL LaTeX style files tailored for this year's conference. Submissions must conform to the official style guidelines. Please see information about paper formatting requirements and style at http://www.acl2019.org/EN/call-for-papers.xhtml. Scroll down to “Paper Submission and Templates.”

Submissions need to be anonymous.

Dual submission policy

Papers may NOT be submitted to the BioNLP 2019 workshop if they are or will be concurrently submitted to another meeting or publication.

MEDIQA 2019

A BioNLP-19 shared task on textual inference and question entailment

In 2019, the workshop will present the results of the shared task on biomedical textual inference and question entailment. See details at https://sites.google.com/view/mediqa2019