Difference between revisions of "BioNLP 2023"

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*April 10, 2022: Camera-ready papers due
 
*April 10, 2022: Camera-ready papers due
 
*BioNLP 2022 Workshop at ACL, May 26, 2022, Dublin, Ireland
 
*BioNLP 2022 Workshop at ACL, May 26, 2022, Dublin, Ireland
 +
 +
   
 +
<h2>BioNLP 2022: Program</h2>
 +
 +
<h4>All times are Ireland timezone (GMT+1)</h4>
 +
 +
 +
<table cellspacing="0" cellpadding="2" border="0" valuing="top" width="90%">
 +
<tr>
 +
<td>09:00–09:10</td><td><b>Opening remarks</b></td>
 +
</tr>
 +
<tr>
 +
<td nowrap valign=top bgcolor=#ededed><b>09:10–10:30</b></td>
 +
<td valign=top bgcolor=#ededed>
 +
<b>Session 1: Question Answering, Discourse Structure and Clinical Applications (Onsite oral presentations) </b>
 +
</td>
 +
</tr>
 +
<tr>
 +
  <td nowrap valign=top>09:10–9:30 </td>
 +
  <td valign=top><b>Explainable Assessment of Healthcare Articles with QA</b>
 +
  <br> <i>Alodie Boissonnet<sup>1</sup>,&nbsp;Marzieh Saeidi<sup>2</sup>,&nbsp;Vassilis Plachouras<sup>2</sup>,&nbsp;Andreas Vlachos<sup>1</sup></i><br>
 +
  <sup>1</sup>University of Cambridge, <sup>2</sup>Facebook
 +
</td>
 +
      </tr>
 +
<tr>
 +
  <td nowrap valign=top>09:30–9:50</td>
 +
<td valign=top><b>A sequence-to-sequence approach for document-level relation extraction</b>
 +
<br>
 +
<i>John Giorgi<sup>1</sup>,&nbsp;Gary Bader<sup>1</sup>,&nbsp;Bo Wang<sup>2</sup></i><br>
 +
  <sup>1</sup>University of Toronto, <sup>2</sup>School of Artificial Intelligence, Jilin University
 +
</td>
 +
      </tr>
 +
  <tr>
 +
<td nowrap valign=top>
 +
  09:50–10:10
 +
</td>
 +
<td valign=top> <b>Position-based Prompting for Health Outcome Generation</b>
 +
  <br>
 +
  <i>Micheal Abaho<sup>1</sup>,&nbsp;Danushka Bollegala<sup>2</sup>,&nbsp;Paula Williamson<sup>1</sup>,&nbsp;Susanna Dodd<sup>1</sup></i><br>
 +
  <sup>1</sup>University of Liverpool, <sup>2</sup>University of Liverpool/Amazon
 +
</td>
 +
      </tr>
 +
    <tr>
 +
<td nowrap valign=top>
 +
    10:10-10:30
 +
</td>
 +
<td valign=top >
 +
    <b>How You Say It Matters: Measuring the Impact of Verbal Disfluency Tags on Automated Dementia Detection</b>
 +
  <br>
 +
  <i>Shahla Farzana<sup>1</sup>,&nbsp;Ashwin Deshpande<sup>1</sup>,&nbsp;Natalie Parde<sup>2</sup></i><br>
 +
  <sup>1</sup>University of Illinois Chicago, <sup>2</sup>University of Illinois at Chicago
 +
</td>
 +
      </tr>
 +
 +
<tr>
 +
<td nowrap valign=top bgcolor=#ededed>
 +
<b>10:30–11:00</b>
 +
</td>
 +
<td valign=top bgcolor=#ededed>
 +
<b><em>Coffee Break</em></b>
 +
</td>
 +
</tr>
 +
<tr>
 +
<td valign=top style="padding-top: 14px;">11:00–12:30</td>
 +
<td valign=top style="padding-top: 14px;">
 +
<b>Hybrid Poster Session 1</b>
 +
</td>
 +
</tr>
 +
  <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>Data Augmentation for Biomedical Factoid Question Answering</b>
 +
  <br>
 +
  <em>Dimitris Pappas<sup>1</sup>,&nbsp;Prodromos Malakasiotis<sup>2</sup>,&nbsp;Ion Androutsopoulos<sup>1</sup></em><br>
 +
  <sup>1</sup>Athens University of Economics and Business, <sup>2</sup>Institute of Informatics & Telecommunications, NCSR "Demokritos", Athens University of Economics and Business Informatics Department
 +
</td>
 +
      </tr>
 +
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>Slot Filling for Biomedical Information Extraction</b>
 +
  <br>
 +
  <em>Yannis Papanikolaou<sup>1</sup>,&nbsp;Marlene Staib<sup>1</sup>,&nbsp;Justin Grace<sup>2</sup>,&nbsp;Francine Bennett<sup>1</sup></em><br>
 +
  <sup>1</sup>Healx Ltd, <sup>2</sup>Healx.ltd
 +
</td>
 +
      </tr>
 +
 +
  <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>Automatic Biomedical Term Clustering by Learning Fine-grained Term Representations</b>
 +
  <br>
 +
  <em>Sihang Zeng,&nbsp;Zheng Yuan,&nbsp;Sheng Yu</em><br>
 +
  Tsinghua University
 +
</td>
 +
      </tr>
 +
 +
<tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>BioBART: Pretraining and Evaluation of A Biomedical Generative Language Model</b>
 +
  <br>
 +
  <em>Hongyi Yuan<sup>1</sup>,&nbsp;Zheng Yuan<sup>1</sup>,&nbsp;Ruyi Gan<sup>2</sup>,&nbsp;Jiaxing Zhang<sup>2</sup>,&nbsp;Yutao Xie<sup>2</sup>,&nbsp;Sheng Yu<sup>1</sup></em><br>
 +
  <sup>1</sup>Tsinghua University, <sup>2</sup>International Digital Economy Academy
 +
</td>
 +
      </tr>
 +
 +
  <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>Incorporating Medical Knowledge to Transformer-based Language Models for Medical Dialogue Generation</b>
 +
  <br>
 +
  <em>Usman Naseem<sup>1</sup>,&nbsp;Ajay Bandi<sup>2</sup>,&nbsp;Shaina Raza<sup>3</sup>,&nbsp;Junaid Rashid<sup>4</sup>,&nbsp;Bharathi Raja Chakravarthi<sup>5</sup></em><br>
 +
  <sup>1</sup>University of Sydney, <sup>2</sup>School of Computer Science and Information Systems Northwest Missouri State University Maryville, MO 64468 USA, <sup>3</sup>Health Systems Impact Fellow, University of Toronto  Toronto, Ontario, Canada, <sup>4</sup>Department of Computer Science and Engineering, Kongju National University, South Korea, <sup>5</sup>Data Science Institute, National University of Ireland Galway, Galway, Ireland
 +
</td>
 +
      </tr>
 +
 +
      <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>Memory-aligned Knowledge Graph for Clinically Accurate Radiology Image Report Generation</b>
 +
  <br>
 +
  <em>Sixing Yan</em><br>
 +
  Hong Kong Baptist University
 +
</td>
 +
      </tr>
 +
 +
  <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>Simple Semantic-based Data Augmentation for Named Entity Recognition in Biomedical Texts</b>
 +
  <br>
 +
  <em>Uyen Phan<sup>1</sup> and Nhung Nguyen<sup>2</sup></em><br>
 +
  <sup>1</sup>VNUHCM-University of Science, <sup>2</sup>The University of Manchester
 +
</td>
 +
      </tr>
 +
 +
  <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>Auxiliary Learning for Named Entity Recognition with Multiple Auxiliary Biomedical Training Data</b>
 +
<br>
 +
  <em>Taiki Watanabe<sup>1</sup>,&nbsp;Tomoya Ichikawa<sup>2</sup>,&nbsp;Akihiro Tamura<sup>2</sup>,&nbsp;Tomoya Iwakura<sup>3</sup>,&nbsp;Chunpeng Ma<sup>1</sup>,&nbsp;Tsuneo Kato<sup>2</sup></em><br>
 +
  <sup>1</sup>Fujitsu Ltd., <sup>2</sup>Doshisha University, <sup>3</sup>Fujitsu
 +
</td>
 +
      </tr>
 +
 +
    <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>SNP2Vec: Scalable Self-Supervised Pre-Training for Genome-Wide Association Study</b>
 +
  <br>
 +
  <em>Samuel Cahyawijaya<sup>1</sup>,&nbsp;Tiezheng Yu<sup>2</sup>,&nbsp;Zihan Liu<sup>3</sup>,&nbsp;Xiaopu ZHOU<sup>4</sup>,&nbsp;Tze Wing MAK<sup>4</sup>,&nbsp;Yuk Yu IP<sup>4</sup>,&nbsp;Pascale Fung<sup>3</sup></em><br>
 +
  <sup>1</sup>HKUST, <sup>2</sup>The Hong Kong University of Science and Technology, <sup>3</sup>Hong Kong University of Science and Technology, <sup>4</sup>Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience Center, The Hong Kong University of Science and Technology, Hong Kong, China
 +
</td>
 +
      </tr>
 +
 +
  <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>Biomedical NER using Novel Schema and Distant Supervision</b>
 +
  <br>
 +
  <em>Anshita Khandelwal,&nbsp;Alok Kar,&nbsp;Veera Chikka,&nbsp;Kamalakar Karlapalem</em><br>
 +
  International Institute of Information Technology
 +
</td>
 +
      </tr>
 +
 +
    <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>Improving Supervised Drug-Protein Relation Extraction with Distantly Supervised Models</b>
 +
  <br>
 +
  <em>Naoki Iinuma,&nbsp;Makoto Miwa,&nbsp;Yutaka Sasaki</em><br>
 +
  Toyota Technological Institute
 +
</td>
 +
      </tr>
 +
 +
  <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>Named Entity Recognition for Cancer Immunology Research Using Distant Supervision</b>
 +
  <br>
 +
  <em>Hai-Long Trieu<sup>1</sup>,&nbsp;Makoto Miwa<sup>2</sup>,&nbsp;Sophia Ananiadou<sup>3</sup></em><br>
 +
  <sup>1</sup>National Institute of Advanced Industrial Science and Technology, <sup>2</sup>Toyota Technological Institute, <sup>3</sup>University of Manchester
 +
</td>
 +
      </tr>
 +
 +
  <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>Intra-Template Entity Compatibility based Slot-Filling for Clinical Trial Information Extraction</b>
 +
  <br>
 +
  <em>Christian Witte and Philipp Cimiano</em><br>
 +
  Bielefeld University
 +
</td>
 +
      </tr>
 +
 +
  <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>Pretrained Biomedical Language Models for Clinical NLP in Spanish</b>
 +
  <br>
 +
  <em>Casimiro Pio Carrino<sup>1</sup>,&nbsp;Joan Llop<sup>2</sup>,&nbsp;Marc Pàmies<sup>2</sup>,&nbsp;Asier Gutiérrez-Fandiño<sup>2</sup>,&nbsp;Jordi Armengol-Estapé<sup>2</sup>,&nbsp;Joaquín Silveira-Ocampo<sup>1</sup>,&nbsp;Alfonso Valencia<sup>1</sup>,&nbsp;Aitor Gonzalez-Agirre<sup>1</sup>,&nbsp;Marta Villegas<sup>2</sup></em><br>
 +
  <sup>1</sup>Barcelona Supercomputing Center (BSC), <sup>2</sup>Barcelona Supercomputing Center
 +
</td>
 +
      </tr>
 +
    <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>Zero-Shot Aspect-Based Scientific Document Summarization using Self-Supervised Pre-training</b>
 +
  <br>
 +
  <em>Amir Soleimani<sup>1</sup>,&nbsp;Vassilina Nikoulina<sup>2</sup>,&nbsp;Benoit Favre<sup>3</sup>,&nbsp;Salah Ait Mokhtar<sup>2</sup></em><br>
 +
  <sup>1</sup>University of Amsterdam, <sup>2</sup>Naver Labs Europe, <sup>3</sup>Aix Marseille Univ, Université de Toulon, CNRS, LIS, Marseille, France
 +
</td>
 +
      </tr>
 +
 +
    <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>Zero-Shot Aspect-Based Scientific Document Summarization using Self-Supervised Pre-training</b>
 +
  <br>
 +
  <em>Amir Soleimani<sup>1</sup>,&nbsp;Vassilina Nikoulina<sup>2</sup>,&nbsp;Benoit Favre<sup>3</sup>,&nbsp;Salah Ait Mokhtar<sup>2</sup></em><br>
 +
  <sup>1</sup>University of Amsterdam, <sup>2</sup>Naver Labs Europe, <sup>3</sup>Aix Marseille Univ, Université de Toulon, CNRS, LIS, Marseille, France
 +
</td>
 +
      </tr>
 +
 +
    <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>VPAI_Lab at MedVidQA 2022: A Two-Stage Cross-modal Fusion Method for Medical Instructional Video Classification</b>
 +
  <br>
 +
  <em>Bin Li<sup>1</sup>,&nbsp;Yixuan Weng<sup>2</sup>,&nbsp;Fei Xia<sup>3</sup>,&nbsp;Bin Sun<sup>1</sup>,&nbsp;Shutao Li<sup>1</sup></em><br>
 +
  <sup>1</sup>Hunan University, <sup>2</sup>Institute of Automation, Chinese Academy of Sciences, <sup>3</sup>1National Laboratory of Pattern Recognition,Institute of Automation 2University of Chinese Academy of Sciences, Beijing, China
 +
</td>
 +
      </tr>
 +
 +
<tr>
 +
<td valign=top style="padding-top: 14px; bgcolor=#ededed">
 +
<b>12:30–14:00</b>
 +
</td>
 +
<td valign=top style="padding-top: 14px;">
 +
<b><em>Lunch Break</em></b>
 +
</td>
 +
</tr>
 +
<tr>
 +
<td valign=top style="padding-top: 14px;">14:00–15:00</td>
 +
<td valign=top style="padding-top: 14px;">
 +
<b> Summarization and text mining (Onsite oral presentations)  </b>
 +
</td>
 +
</tr>
 +
 +
  <tr>
 +
<td nowrap valign=top>
 +
  14:00-14:20
 +
</td>
 +
<td>
 +
    <b>GenCompareSum: a hybrid unsupervised summarization method using salience</b>
 +
  <br>
 +
  <em>Jennifer Bishop,&nbsp;Qianqian Xie,&nbsp;Sophia Ananiadou</em><br>
 +
  University of Manchester
 +
</td>
 +
      </tr>
 +
 +
  <tr>
 +
<td nowrap valign=top>
 +
    14:20-14:40
 +
</td>
 +
<td>
 +
    <b>BioCite: A Deep Learning-based Citation Linkage Framework for Biomedical Research Articles</b>
 +
  </a><br>
 +
  <em>Sudipta Singha Roy<sup>1</sup> and Robert E. Mercer<sup>2</sup></em><br>
 +
  <sup>1</sup>University of Western Ontario, <sup>2</sup>The University of Western Ontario</a>
 +
</td>
 +
      </tr>
 +
 +
  <tr>
 +
<td nowrap valign=top>
 +
  14:40-15:00
 +
</td>
 +
<td>
 +
    <b>Low Resource Causal Event Detection from Biomedical Literature</b>
 +
  <br>
 +
  <em>Zhengzhong Liang<sup>1</sup>,&nbsp;Enrique Noriega-Atala<sup>2</sup>,&nbsp;Clayton Morrison<sup>1</sup>,&nbsp;Mihai Surdeanu<sup>1</sup></em><br>
 +
  <sup>1</sup>University of Arizona, <sup>2</sup>The University of Arizona
 +
</td>
 +
      </tr>
 +
 +
<tr>
 +
<td valign=top style="padding-top: 14px; bgcolor=#ededed">
 +
<b>15:00–15:30</b>
 +
</td>
 +
<td valign=top style="padding-top: 14px;">
 +
<b><em>Coffee Break</em></b>
 +
</td>
 +
</tr>
 +
<tr>
 +
<td valign=top style="padding-top: 14px;">15:30–17:00</td>
 +
<td valign=top style="padding-top: 14px;">
 +
<b> Hybrid Poster Session 2 </b>
 +
</td>
 +
</tr>
 +
 +
    <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>Overview of the MedVidQA 2022 Shared Task on Medical Video Question-Answering</b>
 +
<br>
 +
  <em>Deepak Gupta and Dina Demner-Fushman</em><br>
 +
  National Library of Medicine, NIH
 +
</td>
 +
      </tr>
 +
 +
  <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>Inter-annotator agreement is not the ceiling of machine learning performance: Evidence from a comprehensive set of simulations</b>
 +
  <br>
 +
  <em>Russell Richie<sup>1</sup>,&nbsp;Sachin Grover<sup>1</sup>,&nbsp;Fuchiang Tsui<sup>2</sup></em><br>
 +
  <sup>1</sup>Children's Hospital of Philadelphia, <sup>2</sup>Children's Hospital of Philadelphia; University of Pennsylvania
 +
</td>
 +
      </tr>
 +
 +
 +
<tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>Conversational Bots for Psychotherapy: A Study of Generative Transformer Models Using Domain-specific Dialogues</b>
 +
  <br>
 +
  <em>Avisha Das<sup>1</sup>,&nbsp;Salih Selek<sup>2</sup>,&nbsp;Alia Warner<sup>2</sup>,&nbsp;Xu Zuo<sup>1</sup>,&nbsp;Yan Hu<sup>1</sup>,&nbsp;Vipina Kuttichi Keloth<sup>1</sup>,&nbsp;Jianfu Li<sup>1</sup>,&nbsp;W. Zheng<sup>1</sup>,&nbsp;Hua Xu<sup>1</sup></em><br>
 +
  <sup>1</sup>School of Biomedical Informatics, UTHealth, <sup>2</sup>McGovern Medical School, UTHealth
 +
</td>
 +
      </tr>
 +
  <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>Inter-annotator agreement is not the ceiling of machine learning performance: Evidence from a comprehensive set of simulations</b>
 +
  <br>
 +
  <em>Russell Richie<sup>1</sup>,&nbsp;Sachin Grover<sup>1</sup>,&nbsp;Fuchiang Tsui<sup>2</sup></em><br>
 +
  <sup>1</sup>Children's Hospital of Philadelphia, <sup>2</sup>Children's Hospital of Philadelphia; University of Pennsylvania
 +
</td>
 +
      </tr>
 +
 +
    <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>BanglaBioMed: A Biomedical Named-Entity Annotated Corpus for Bangla (Bengali)</b>
 +
  <br>
 +
  <em>Salim Sazzed</em><br>
 +
  Old Dominion University
 +
</td>
 +
      </tr>
 +
 +
  <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>BEEDS: Large-Scale Biomedical Event Extraction using Distant Supervision and Question Answering</b>
 +
  <br>
 +
  <em>Xing David Wang,&nbsp;Ulf Leser,&nbsp;Leon Weber</em><br>
 +
  Humboldt-Universität zu Berlin
 +
</td>
 +
      </tr>
 +
 +
  <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>Data Augmentation for Rare Symptoms in Vaccine Side-Effect Detection</b>
 +
  <br>
 +
  <em>Bosung Kim and Ndapa Nakashole</em><br>
 +
  University of California, San Diego
 +
</td>
 +
      </tr>
 +
 +
<tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>ICDBigBird: A Contextual Embedding Model for ICD Code Classification</b>
 +
  <br>
 +
  <em>George Michalopoulos<sup>1</sup>,&nbsp;Michal Malyska<sup>2</sup>,&nbsp;Nicola Sahar<sup>3</sup>,&nbsp;Alexander Wong<sup>1</sup>,&nbsp;Helen Chen<sup>1</sup></em><br>
 +
  <sup>1</sup>University of Waterloo, <sup>2</sup>University of Toronto, <sup>3</sup>Semantic Health
 +
</td>
 +
      </tr>
 +
 +
<tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>Doctor XAvIer: Explainable Diagnosis on Physician-Patient Dialogues and XAI Evaluation</b>
 +
  <br>
 +
  <em>Hillary Ngai<sup>1</sup> and Frank Rudzicz<sup>2</sup></em><br>
 +
  <sup>1</sup>Vector Institute for Artificial Intelligence, <sup>2</sup>Vector Institute for Artificial Intelligence, University of Toronto
 +
</td>
 +
      </tr>
 +
 +
<tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>DISTANT-CTO: A Zero Cost, Distantly Supervised Approach to Improve Low-Resource Entity Extraction Using Clinical Trials Literature</b>
 +
  <br>
 +
  <em>Anjani Dhrangadhariya<sup>1</sup> and Henning Müller<sup>2</sup></em><br>
 +
  <sup>1</sup>HES-SO Valais-Wallis, <sup>2</sup>HES-SO
 +
</td>
 +
      </tr>
 +
 +
  <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>Improving Romanian BioNER Using a Biologically Inspired System</b>
 +
  <br>
 +
  <em>Maria Mitrofan<sup>1</sup> and Vasile Pais<sup>2</sup></em><br>
 +
  <sup>1</sup>RACAI, <sup>2</sup>Research Institute for Artificial Intelligence, Romanian Academy
 +
</td>
 +
      </tr>
 +
 +
<tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>EchoGen: Generating Conclusions from Echocardiogram Notes</b>
 +
  <br>
 +
  <em>Liyan Tang<sup>1</sup>,&nbsp;Shravan Kooragayalu<sup>2</sup>,&nbsp;Yanshan Wang<sup>2</sup>,&nbsp;Ying Ding<sup>1</sup>,&nbsp;Greg Durrett<sup>3</sup>,&nbsp;Justin Rousseau<sup>1</sup>,&nbsp;Yifan Peng<sup>4</sup></em><br>
 +
  <sup>1</sup>University of Texas at Austin, <sup>2</sup>University of Pittsburgh, <sup>3</sup>UT Austin, <sup>4</sup>Cornell Medicine
 +
</td>
 +
      </tr>
 +
 +
<tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>Quantifying Clinical Outcome Measures in Patients with Epilepsy Using the Electronic Health Record</b>
 +
  <br>
 +
  <em>Kevin Xie<sup>1</sup>,&nbsp;Brian Litt<sup>2</sup>,&nbsp;Dan Roth<sup>1</sup>,&nbsp;Colin Ellis<sup>2</sup></em><br>
 +
  <sup>1</sup>University of Pennsylvania, <sup>2</sup>Perelman School of Medicine, University of Pennsylvania
 +
</td>
 +
      </tr>
 +
 +
  <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>Comparing Encoder-Only and Encoder-Decoder Transformers for Relation Extraction from Biomedical Texts: An Empirical Study on Ten Benchmark Datasets</b>
 +
  <br>
 +
  <em>Mourad Sarrouti,&nbsp;Carson Tao,&nbsp;Yoann Mamy Randriamihaja</em><br>
 +
  Sumitovant Biopharma
 +
</td>
 +
      </tr>
 +
 +
  <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>Utility Preservation of Clinical Text After De-Identification</b>
 +
  <br>
 +
  <em>Thomas Vakili<sup>1</sup> and Hercules Dalianis<sup>2</sup></em><br>
 +
  <sup>1</sup>Department of Computer and Systems Sciences, Stockholm University, <sup>2</sup>DSV/Stockholm University
 +
</td>
 +
      </tr>
 +
 +
  <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>Horses to Zebras: Ontology-Guided Data Augmentation and Synthesis for ICD-9 Coding</b>
 +
  <br>
 +
  <em>Matúš Falis<sup>1</sup>,&nbsp;Hang Dong<sup>2</sup>,&nbsp;Alexandra Birch<sup>1</sup>,&nbsp;Beatrice Alex<sup>1</sup></em><br>
 +
  <sup>1</sup>The University of Edinburgh, <sup>2</sup>Oxford University
 +
</td>
 +
      </tr>
 +
 +
  <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>Towards Automatic Curation of Antibiotic Resistance Genes via Statement Extraction from Scientific Papers: A Benchmark Dataset and Models</b>
 +
  <br>
 +
  <em>Sidhant Chandak<sup>1</sup>,&nbsp;Liqing Zhang<sup>2</sup>,&nbsp;Connor Brown<sup>2</sup>,&nbsp;Lifu Huang<sup>2</sup></em><br>
 +
  <sup>1</sup>Indian institute of Technology Kanpur, <sup>2</sup>Virginia Tech
 +
</td>
 +
      </tr>
 +
 +
  <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>Model Distillation for Faithful Explanations of Medical Code Predictions</b>
 +
  <br>
 +
  <em>Zach Wood-Doughty,&nbsp;Isabel Cachola,&nbsp;Mark Dredze</em><br>
 +
  Johns Hopkins University
 +
</td>
 +
      </tr>
 +
 +
    <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>Towards Generalizable Methods for Automating Risk Score Calculation</b>
 +
  <br>
 +
  <em>Jennifer J Liang<sup>1</sup>,&nbsp;Eric Lehman<sup>2</sup>,&nbsp;Ananya Iyengar<sup>3</sup>,&nbsp;Diwakar Mahajan<sup>1</sup>,&nbsp;Preethi Raghavan<sup>1</sup>,&nbsp;Cindy Y. Chang<sup>4</sup>,&nbsp;Peter Szolovits<sup>2</sup></em><br>
 +
  <sup>1</sup>IBM Research, <sup>2</sup>MIT, <sup>3</sup>Northeastern University, <sup>4</sup>Brigham and Women's Hospital
 +
</td>
 +
      </tr>
 +
 +
    <tr>
 +
<td nowrap valign=top>
 +
  &nbsp;&nbsp;
 +
</td>
 +
<td>
 +
    <b>DoSSIER at MedVidQA 2022: Text-based Approaches to Medical Video Answer Localization Problem</b>
 +
  <br>
 +
  <em>Wojciech Kusa<sup>1</sup>,&nbsp;Georgios Peikos<sup>2</sup>,&nbsp;Óscar Espitia<sup>3</sup>,&nbsp;Allan Hanbury<sup>1</sup>,&nbsp;Gabriella Pasi<sup>4</sup></em><br>
 +
  <sup>1</sup>TU Wien, <sup>2</sup>University of Milano-Bicocca, <sup>3</sup>University of Milano Bicocca, <sup>4</sup>Università degli Studi di Milano Bicocca
 +
</td>
 +
      </tr>
 +
 +
</table>
  
 
===Submission Types & Requirements ===
 
===Submission Types & Requirements ===

Revision as of 23:34, 16 April 2022

SIGBIOMED 

BIONLP 2022 @ ACL 2022

The 21st BioNLP workshop associated with the ACL SIGBIOMED special interest group is co-located with ACL 2022

IMPORTANT DATES

  • March 7, 2022: Workshop Paper Due Date
  • Submission site: https://www.softconf.com/acl2022/BioNLP2022
  • March 28, 2022: Notification of Acceptance
  • April 10, 2022: Camera-ready papers due
  • BioNLP 2022 Workshop at ACL, May 26, 2022, Dublin, Ireland


BioNLP 2022: Program

All times are Ireland timezone (GMT+1)


09:00–09:10Opening remarks
09:10–10:30

Session 1: Question Answering, Discourse Structure and Clinical Applications (Onsite oral presentations)

09:10–9:30 Explainable Assessment of Healthcare Articles with QA 
 
 Alodie Boissonnet1, Marzieh Saeidi2, Vassilis Plachouras2, Andreas Vlachos1

1University of Cambridge, 2Facebook

09:30–9:50 A sequence-to-sequence approach for document-level relation extraction


John Giorgi1, Gary Bader1, Bo Wang2
1University of Toronto, 2School of Artificial Intelligence, Jilin University

09:50–10:10

Position-based Prompting for Health Outcome Generation


Micheal Abaho1, Danushka Bollegala2, Paula Williamson1, Susanna Dodd1
1University of Liverpool, 2University of Liverpool/Amazon

10:10-10:30

How You Say It Matters: Measuring the Impact of Verbal Disfluency Tags on Automated Dementia Detection
Shahla Farzana1, Ashwin Deshpande1, Natalie Parde2
1University of Illinois Chicago, 2University of Illinois at Chicago

10:30–11:00

Coffee Break

11:00–12:30

Hybrid Poster Session 1

  

Data Augmentation for Biomedical Factoid Question Answering
Dimitris Pappas1, Prodromos Malakasiotis2, Ion Androutsopoulos1
1Athens University of Economics and Business, 2Institute of Informatics & Telecommunications, NCSR "Demokritos", Athens University of Economics and Business Informatics Department

  

Slot Filling for Biomedical Information Extraction
Yannis Papanikolaou1, Marlene Staib1, Justin Grace2, Francine Bennett1
1Healx Ltd, 2Healx.ltd

  

Automatic Biomedical Term Clustering by Learning Fine-grained Term Representations
Sihang Zeng, Zheng Yuan, Sheng Yu
Tsinghua University

  

BioBART: Pretraining and Evaluation of A Biomedical Generative Language Model
Hongyi Yuan1, Zheng Yuan1, Ruyi Gan2, Jiaxing Zhang2, Yutao Xie2, Sheng Yu1
1Tsinghua University, 2International Digital Economy Academy

  

Incorporating Medical Knowledge to Transformer-based Language Models for Medical Dialogue Generation
Usman Naseem1, Ajay Bandi2, Shaina Raza3, Junaid Rashid4, Bharathi Raja Chakravarthi5
1University of Sydney, 2School of Computer Science and Information Systems Northwest Missouri State University Maryville, MO 64468 USA, 3Health Systems Impact Fellow, University of Toronto Toronto, Ontario, Canada, 4Department of Computer Science and Engineering, Kongju National University, South Korea, 5Data Science Institute, National University of Ireland Galway, Galway, Ireland

  

Memory-aligned Knowledge Graph for Clinically Accurate Radiology Image Report Generation
Sixing Yan
Hong Kong Baptist University

  

Simple Semantic-based Data Augmentation for Named Entity Recognition in Biomedical Texts
Uyen Phan1 and Nhung Nguyen2
1VNUHCM-University of Science, 2The University of Manchester

  

Auxiliary Learning for Named Entity Recognition with Multiple Auxiliary Biomedical Training Data
Taiki Watanabe1, Tomoya Ichikawa2, Akihiro Tamura2, Tomoya Iwakura3, Chunpeng Ma1, Tsuneo Kato2
1Fujitsu Ltd., 2Doshisha University, 3Fujitsu

  

SNP2Vec: Scalable Self-Supervised Pre-Training for Genome-Wide Association Study
Samuel Cahyawijaya1, Tiezheng Yu2, Zihan Liu3, Xiaopu ZHOU4, Tze Wing MAK4, Yuk Yu IP4, Pascale Fung3
1HKUST, 2The Hong Kong University of Science and Technology, 3Hong Kong University of Science and Technology, 4Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience Center, The Hong Kong University of Science and Technology, Hong Kong, China

  

Biomedical NER using Novel Schema and Distant Supervision
Anshita Khandelwal, Alok Kar, Veera Chikka, Kamalakar Karlapalem
International Institute of Information Technology

  

Improving Supervised Drug-Protein Relation Extraction with Distantly Supervised Models
Naoki Iinuma, Makoto Miwa, Yutaka Sasaki
Toyota Technological Institute

  

Named Entity Recognition for Cancer Immunology Research Using Distant Supervision
Hai-Long Trieu1, Makoto Miwa2, Sophia Ananiadou3
1National Institute of Advanced Industrial Science and Technology, 2Toyota Technological Institute, 3University of Manchester

  

Intra-Template Entity Compatibility based Slot-Filling for Clinical Trial Information Extraction
Christian Witte and Philipp Cimiano
Bielefeld University

  

Pretrained Biomedical Language Models for Clinical NLP in Spanish
Casimiro Pio Carrino1, Joan Llop2, Marc Pàmies2, Asier Gutiérrez-Fandiño2, Jordi Armengol-Estapé2, Joaquín Silveira-Ocampo1, Alfonso Valencia1, Aitor Gonzalez-Agirre1, Marta Villegas2
1Barcelona Supercomputing Center (BSC), 2Barcelona Supercomputing Center

  

Zero-Shot Aspect-Based Scientific Document Summarization using Self-Supervised Pre-training
Amir Soleimani1, Vassilina Nikoulina2, Benoit Favre3, Salah Ait Mokhtar2
1University of Amsterdam, 2Naver Labs Europe, 3Aix Marseille Univ, Université de Toulon, CNRS, LIS, Marseille, France

  

Zero-Shot Aspect-Based Scientific Document Summarization using Self-Supervised Pre-training
Amir Soleimani1, Vassilina Nikoulina2, Benoit Favre3, Salah Ait Mokhtar2
1University of Amsterdam, 2Naver Labs Europe, 3Aix Marseille Univ, Université de Toulon, CNRS, LIS, Marseille, France

  

VPAI_Lab at MedVidQA 2022: A Two-Stage Cross-modal Fusion Method for Medical Instructional Video Classification
Bin Li1, Yixuan Weng2, Fei Xia3, Bin Sun1, Shutao Li1
1Hunan University, 2Institute of Automation, Chinese Academy of Sciences, 31National Laboratory of Pattern Recognition,Institute of Automation 2University of Chinese Academy of Sciences, Beijing, China

12:30–14:00

Lunch Break

14:00–15:00

Summarization and text mining (Onsite oral presentations)

14:00-14:20

GenCompareSum: a hybrid unsupervised summarization method using salience
Jennifer Bishop, Qianqian Xie, Sophia Ananiadou
University of Manchester

14:20-14:40

BioCite: A Deep Learning-based Citation Linkage Framework for Biomedical Research Articles </a>
Sudipta Singha Roy1 and Robert E. Mercer2
1University of Western Ontario, 2The University of Western Ontario</a>

14:40-15:00

Low Resource Causal Event Detection from Biomedical Literature
Zhengzhong Liang1, Enrique Noriega-Atala2, Clayton Morrison1, Mihai Surdeanu1
1University of Arizona, 2The University of Arizona

15:00–15:30

Coffee Break

15:30–17:00

Hybrid Poster Session 2

  

Overview of the MedVidQA 2022 Shared Task on Medical Video Question-Answering
Deepak Gupta and Dina Demner-Fushman
National Library of Medicine, NIH

  

Inter-annotator agreement is not the ceiling of machine learning performance: Evidence from a comprehensive set of simulations
Russell Richie1, Sachin Grover1, Fuchiang Tsui2
1Children's Hospital of Philadelphia, 2Children's Hospital of Philadelphia; University of Pennsylvania

  

Conversational Bots for Psychotherapy: A Study of Generative Transformer Models Using Domain-specific Dialogues
Avisha Das1, Salih Selek2, Alia Warner2, Xu Zuo1, Yan Hu1, Vipina Kuttichi Keloth1, Jianfu Li1, W. Zheng1, Hua Xu1
1School of Biomedical Informatics, UTHealth, 2McGovern Medical School, UTHealth

  

Inter-annotator agreement is not the ceiling of machine learning performance: Evidence from a comprehensive set of simulations
Russell Richie1, Sachin Grover1, Fuchiang Tsui2
1Children's Hospital of Philadelphia, 2Children's Hospital of Philadelphia; University of Pennsylvania

  

BanglaBioMed: A Biomedical Named-Entity Annotated Corpus for Bangla (Bengali)
Salim Sazzed
Old Dominion University

  

BEEDS: Large-Scale Biomedical Event Extraction using Distant Supervision and Question Answering
Xing David Wang, Ulf Leser, Leon Weber
Humboldt-Universität zu Berlin

  

Data Augmentation for Rare Symptoms in Vaccine Side-Effect Detection
Bosung Kim and Ndapa Nakashole
University of California, San Diego

  

ICDBigBird: A Contextual Embedding Model for ICD Code Classification
George Michalopoulos1, Michal Malyska2, Nicola Sahar3, Alexander Wong1, Helen Chen1
1University of Waterloo, 2University of Toronto, 3Semantic Health

  

Doctor XAvIer: Explainable Diagnosis on Physician-Patient Dialogues and XAI Evaluation
Hillary Ngai1 and Frank Rudzicz2
1Vector Institute for Artificial Intelligence, 2Vector Institute for Artificial Intelligence, University of Toronto

  

DISTANT-CTO: A Zero Cost, Distantly Supervised Approach to Improve Low-Resource Entity Extraction Using Clinical Trials Literature
Anjani Dhrangadhariya1 and Henning Müller2
1HES-SO Valais-Wallis, 2HES-SO

  

Improving Romanian BioNER Using a Biologically Inspired System
Maria Mitrofan1 and Vasile Pais2
1RACAI, 2Research Institute for Artificial Intelligence, Romanian Academy

  

EchoGen: Generating Conclusions from Echocardiogram Notes
Liyan Tang1, Shravan Kooragayalu2, Yanshan Wang2, Ying Ding1, Greg Durrett3, Justin Rousseau1, Yifan Peng4
1University of Texas at Austin, 2University of Pittsburgh, 3UT Austin, 4Cornell Medicine

  

Quantifying Clinical Outcome Measures in Patients with Epilepsy Using the Electronic Health Record
Kevin Xie1, Brian Litt2, Dan Roth1, Colin Ellis2
1University of Pennsylvania, 2Perelman School of Medicine, University of Pennsylvania

  

Comparing Encoder-Only and Encoder-Decoder Transformers for Relation Extraction from Biomedical Texts: An Empirical Study on Ten Benchmark Datasets
Mourad Sarrouti, Carson Tao, Yoann Mamy Randriamihaja
Sumitovant Biopharma

  

Utility Preservation of Clinical Text After De-Identification
Thomas Vakili1 and Hercules Dalianis2
1Department of Computer and Systems Sciences, Stockholm University, 2DSV/Stockholm University

  

Horses to Zebras: Ontology-Guided Data Augmentation and Synthesis for ICD-9 Coding
Matúš Falis1, Hang Dong2, Alexandra Birch1, Beatrice Alex1
1The University of Edinburgh, 2Oxford University

  

Towards Automatic Curation of Antibiotic Resistance Genes via Statement Extraction from Scientific Papers: A Benchmark Dataset and Models
Sidhant Chandak1, Liqing Zhang2, Connor Brown2, Lifu Huang2
1Indian institute of Technology Kanpur, 2Virginia Tech

  

Model Distillation for Faithful Explanations of Medical Code Predictions
Zach Wood-Doughty, Isabel Cachola, Mark Dredze
Johns Hopkins University

  

Towards Generalizable Methods for Automating Risk Score Calculation
Jennifer J Liang1, Eric Lehman2, Ananya Iyengar3, Diwakar Mahajan1, Preethi Raghavan1, Cindy Y. Chang4, Peter Szolovits2
1IBM Research, 2MIT, 3Northeastern University, 4Brigham and Women's Hospital

  

DoSSIER at MedVidQA 2022: Text-based Approaches to Medical Video Answer Localization Problem
Wojciech Kusa1, Georgios Peikos2, Óscar Espitia3, Allan Hanbury1, Gabriella Pasi4
1TU Wien, 2University of Milano-Bicocca, 3University of Milano Bicocca, 4Università degli Studi di Milano Bicocca

Submission Types & Requirements

Following the previous conferences, BioNLP 2022 will be open for two types of submissions: long and short papers. Please follow ACL guidelines https://acl-org.github.io/ACLPUB/formatting.html and templates: https://github.com/acl-org/acl-style-files

Overleaf templates: https://www.overleaf.com/project/5f64f1fb97c4c50001b60549

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.

BioNLP 2022 will be particularly interested in work on detection and mitigation of bias, BioNLP research in languages other than English, particularly, under-represented languages, and health disparities.

Other 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;
  • 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;
  • 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.






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