BioNLP 2023

SIGBIOMED

BIONLP 2021 @ NAACL 2021

All times are in Pacific Time (Seattle, San Francisco, Los Angeles)

Friday June 11, 2021
	08:00–08:15 Opening remarks
	08:15–09:15 Session 1: Information Extraction
08:15–08:30	Improving BERT Model Using Contrastive Learning for Biomedical Relation Extraction Peng Su, Yifan Peng and K. Vijay-Shanker
08:30–08:45	Triplet-Trained Vector Space and Sieve-Based Search Improve Biomedical Concept Normalization Dongfang Xu and Steven Bethard
08:45–09:00	Scalable Few-Shot Learning of Robust Biomedical Name Representations Pieter Fivez, Simon Suster and Walter Daelemans
09:00–09:15	SAFFRON: tranSfer leArning For Food-disease RelatiOn extractioN Gjorgjina Cenikj, Tome Eftimov and Barbara Koroušić Seljak
	09:15–10:00 Session 2: Clinical NLP
09:15–09:30	Are we there yet? Exploring clinical domain knowledge of BERT models Madhumita Sushil, Simon Suster and Walter Daelemans
09:30–09:45	Towards BERT-based Automatic ICD Coding: Limitations and Opportunities Damian Pascual, Sandro Luck and Roger Wattenhofer
09:45–10:00	emrKBQA: A Clinical Knowledge-Base Question Answering Dataset Preethi Raghavan, Jennifer J Liang, Diwakar Mahajan, Rachita Chandra and Peter Szolovits
10:00–10:30	Coffee Break
	Session 3: MEDIQA 2021 Overview: Asma Ben Abacha
10:30–11:00	Overview of the MEDIQA 2021 Shared Task on Summarization in the Medical Domain Asma Ben Abacha, Yassine Mrabet, Yuhao Zhang, Chaitanya Shivade, Curtis Langlotz and Dina Demner-Fushman
	11:00–12:00 Session 4: MEDIQA 2021 Presentations
11:00–11:15	WBI at MEDIQA 2021: Summarizing Consumer Health Questions with Generative Transformers Mario Sänger, Leon Weber and Ulf Leser
11:15–11:30	paht_nlp @ MEDIQA 2021: Multi-grained Query Focused Multi-Answer Summarization Wei Zhu, Yilong He, Ling Chai, Yunxiao Fan, Yuan Ni, GUOTONG XIE and Xiaoling Wang
11:30–11:45	BDKG at MEDIQA 2021: System Report for the Radiology Report Summarization Task Songtai Dai, Quan Wang, Yajuan Lyu and Yong Zhu
11:45–12:00	damo_nlp at MEDIQA 2021: Knowledge-based Preprocessing and Coverage-oriented Reranking for Medical Question Summarization Yifan He, Mosha Chen and Songfang Huang
12:00–12:30	Coffee Break
	12:30–14:30 Session 5: Poster session 1
	Stress Test Evaluation of Biomedical Word Embeddings Vladimir Araujo, Andrés Carvallo, Carlos Aspillaga, Camilo Thorne and Denis Parra
	BLAR: Biomedical Local Acronym Resolver William Hogan, Yoshiki Vazquez Baeza, Yannis Katsis, Tyler Baldwin, Ho-Cheol Kim and Chun-Nan Hsu
	Claim Detection in Biomedical Twitter Posts Amelie Wührl and Roman Klinger
	BioELECTRA:Pretrained Biomedical text Encoder using Discriminators Kamal raj Kanakarajan, Bhuvana Kundumani and Malaikannan Sankarasubbu
	Word centrality constrained representation for keyphrase extraction Zelalem Gero and Joyce Ho
	End-to-end Biomedical Entity Linking with Span-based Dictionary Matching Shogo Ujiie, Hayate Iso, Shuntaro Yada, Shoko Wakamiya and Eiji ARAMAKI
	Word-Level Alignment of Paper Documents with their Electronic Full-Text Counterparts Mark-Christoph Müller, Sucheta Ghosh, Ulrike Wittig and Maja Rey
	Improving Biomedical Pretrained Language Models with Knowledge Zheng Yuan, Yijia Liu, Chuanqi Tan, Songfang Huang and Fei Huang
	EntityBERT: Entity-centric Masking Strategy for Model Pretraining for the Clinical Domain Chen Lin, Timothy Miller, Dmitriy Dligach, Steven Bethard and Guergana Savova
	Contextual explanation rules for neural clinical classifiers Madhumita Sushil, Simon Suster and Walter Daelemans
	Exploring Word Segmentation and Medical Concept Recognition for Chinese Medical Texts Yang Liu, Yuanhe Tian, Tsung-Hui Chang, Song Wu, Xiang Wan and Yan Song
	BioM-Transformers: Building Large Biomedical Language Models with BERT, ALBERT and ELECTRA Sultan Alrowili and Vijay Shanker
	Semi-Supervised Language Models for Identification of Personal Health Experiential from Twitter Data: A Case for Medication Effects Minghao Zhu and Keyuan Jiang
	Context-aware query design combines knowledge and data for efficient reading and reasoning Emilee Holtzapple, Brent Cochran and Natasa Miskov-Zivanov
	Measuring the relative importance of full text sections for information retrieval from scientific literature. Lana Yeganova, Won Gyu KIM, Donald Comeau, W John Wilbur and Zhiyong Lu
14:30–15:00	Coffee Break
	15:00–17:00 Session 7: MEDIQA 2021 Poster Session
	UCSD-Adobe at MEDIQA 2021: Transfer Learning and Answer Sentence Selection for Medical Summarization Khalil Mrini, Franck Dernoncourt, Seunghyun Yoon, Trung Bui, Walter Chang, Emilias Farcas and Ndapa Nakashole
	ChicHealth @ MEDIQA 2021: Exploring the limits of pre-trained seq2seq models for medical summarization Liwen Xu, Yan Zhang, Lei Hong, Yi Cai and Szui Sung
	NCUEE-NLP at MEDIQA 2021: Health Question Summarization Using PEGASUS Transformers Lung-Hao Lee, Po-Han Chen, Yu-Xiang Zeng, Po-Lei Lee and Kuo-Kai Shyu
	SB_NITK at MEDIQA 2021: Leveraging Transfer Learning for Question Summarization in Medical Domain Spandana Balumuri, Sony Bachina and Sowmya Kamath S
	Optum at MEDIQA 2021: Abstractive Summarization of Radiology Reports using simple BART Finetuning Ravi Kondadadi, Sahil Manchanda, Jason Ngo and Ronan McCormack
	QIAI at MEDIQA 2021: Multimodal Radiology Report Summarization Jean-Benoit Delbrouck, Cassie Zhang and Daniel Rubin
	NLM at MEDIQA 2021: Transfer Learning-based Approaches for Consumer Question and Multi-Answer Summarization Shweta Yadav, Mourad Sarrouti and Deepak Gupta
	IBMResearch at MEDIQA 2021: Toward Improving Factual Correctness of Radiology Report Abstractive Summarization Diwakar Mahajan, Ching-Huei Tsou and Jennifer J Liang
	UETrice at MEDIQA 2021: A Prosper-thy-neighbour Extractive Multi-document Summarization Model Duy-Cat Can, Quoc-An Nguyen, Quoc-Hung Duong, Minh-Quang Nguyen, Huy-Son Nguyen, Linh Nguyen Tran Ngoc, Quang-Thuy Ha and Mai-Vu Tran
	MNLP at MEDIQA 2021: Fine-Tuning PEGASUS for Consumer Health Question Summarization Jooyeon Lee, Huong Dang, Ozlem Uzuner and Sam Henry
	UETfishes at MEDIQA 2021: Standing-on-the-Shoulders-of-Giants Model for Abstractive Multi-answer Summarization Hoang-Quynh Le, Quoc-An Nguyen, Quoc-Hung Duong, Minh-Quang Nguyen, Huy-Son Nguyen, Tam Doan Thanh, Hai-Yen Thi Vuong and Trang M. Nguyen
	Session 8: Invited Talk by Makoto Miwa
17:00–17:30	Makoto Miwa: Information Extraction from Texts Using Heterogeneous Information
	17:30–18:00 Closing remarks

IMPORTANT DATES

• Submission deadline: March 20, 2021 11:59 PM Eastern US https://www.softconf.com/naacl2021/bionlp21/
• Notification of acceptance: April 15, 2021
• Camera-ready copy due from authors: April 26, 2021 (HARD DEADLINE)
• Workshop: June 11, 2021

Final papers should match the NAACL 2021 style guide and instructions for formatting: https://2021.naacl.org/calls/style-and-formatting/ General *ACL guidelines for formatting: https://acl-org.github.io/ACLPUB/formatting.html

Shared Task

MEDIQA 2021 The second edition of the MEDIQA challenge collocated with the BioNLP 2021Workshop focuses on summarization in the medical domain with three tasks:

• Consumer health question summarization
• Multi-answer summarization
• Radiology report summarization

Please check the website for details on the tasks, datasets, and submission guidelines: https://sites.google.com/view/mediqa2021

Submission Types & Requirements

Following the previous conferences, BioNLP 2021 will be open for two types of submissions: long and short papers. For the shared task, please select the "long - shared task" submission type. Please use tNAACL instructions and templates: https://2021.naacl.org/calls/style-and-formatting/ The submission site is now available at https://www.softconf.com/naacl2021/bionlp21/

Program Committee

 * 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  
 * Steven Bethard, University of Arizona, USA
 * 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 
 * Kevin Bretonnel Cohen, University of Colorado School of Medicine, USA 
 * Brian Connolly, Kroger Digital, USA 
 * Dina Demner-Fushman, US National Library of Medicine 
 * Bart Desmet, Clinical Center, National Institutes of Health, USA
 * 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
 * Antonio Jimeno Yepes, IBM, Melbourne Area, Australia
 * William Kearns, UW Medicine, USA
 * Halil Kilicoglu, University of Illinois at Urbana-Champaign, USA
 * Ari Klein, University of Pennsylvania, USA 
 * André Lamúrias, University of Lisbon, Portugal
 * Alberto Lavelli, FBK-ICT, Italy
 * Robert Leaman, US National Library of Medicine
 * Ulf Leser, Humboldt-Universität zu Berlin, Germany 
 * Timothy Miller, Children’s Hospital Boston, USA 
 * 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, Cornell Medical School, USA 
 * Laura Plaza, UNED, Madrid, Spain
 * Francisco J. Ribadas-Pena, University of Vigo, Spain
 * Fabio Rinaldi,  University of Zurich, Switzerland  
 * Angus Roberts, The University of Sheffield, UK
 * Kirk Roberts, The University of Texas Health Science Center at Houston, USA 
 * Roland Roller, DFKI GmbH, Berlin, Germany
 * Diana Sousa, University of Lisbon, Portugal
 * Karin Verspoor, The University of Melbourne, Australia
 * Davy Weissenbacher, University of Pennsylvania, USA
 * W John Wilbur, US National Library of Medicine 
 * Shankai Yan, US National Library of Medicine 
 * Chrysoula Zerva, National Centre for Text Mining and University of Manchester, UK 
 * Ayah Zirikly, Clinical Center, National Institutes of Health, USA
 * Pierre Zweigenbaum, LIMSI - CNRS, France

Shared Task Program Committee

* Spandana Balumuri, National Institute of Technology Karnataka, Surathkal, India
* Asma Ben Abacha, NLM/NIH
* Yi Cai, Chic Health, Shanghai, China
* Duy-Cat Can, University of Engineering and Technology, Vietnam
* Songtai Dai, Baidu, Inc, Beijing, China
* Jean-Benoit Delbrouck, Stanford University	
* Deepak Gupta, NLM/NIH
* Yifan He, Alibaba Group, Sunnyvale, CA
* Abdullah Faiz Ur Rahman Khilji, National Institute of Technology Silchar, Mumbai, India
* Ravi Kondadadi, Optum
* Jooyeon Lee, George Mason University, Fairfax, VA		
* Lung-Hao Lee, National Central University, Taiwan
* Diwakar Mahajan, IBM Research, Yorktown Heights, NY
* Yassine Mrabet,  NLM/NIH
* Khalil Mrini, University of California, San Diego
* Mourad Sarrouti, NLM/NIH
* Mario Sänger, Humboldt-Universität zu Berlin
* Chaitanya Shivade, Amazon
* Shweta Yadav, NLM/NIH
* Yuhao Zhang, Stanford University
* Wei Zhu, East China Normal University, Shanghai

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. Despite, or maybe due to reaching maturity, the field of Biomedical NLP continues getting stronger. BioNLP welcomes and encourages 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 active areas of research include, but are not limited to:

• 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
• 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
• Explainable models for biomedical NLP
• Multi-modal models for biomedical NLP
• Getting reproducible results
• BioNLP research in languages other than English

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 and University of Manchester, UK

Dual submission policy

Papers may NOT be submitted to the BioNLP 2021 workshop if they are or will be concurrently submitted to another meeting or publication.