Difference between revisions of "BioNLP 2023"

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*'''Workshop: Thursday July 19, 2018'''
 
*'''Workshop: Thursday July 19, 2018'''
  
 
<center>
 
  
 
<h2>BioNLP 2018 WORKSHOP PROGRAM</h2>
 
<h2>BioNLP 2018 WORKSHOP PROGRAM</h2>
  
<table cellspacing="0" cellpadding="5" border="0"><tr><td colspan=2 style="padding-top: 14px;"><h4>Thursday July 19, 2018</h4></td></tr>
+
<table cellspacing="0" cellpadding="5" border="0"><tr><td colspan=2 style="padding-top: 14px;"><b>Thursday July 19, 2018</b></td></tr>
<tr><td valign=top style="padding-top: 14px;"><b>9:00&#8211;9:10</b></td><td valign=top style="padding-top: 14px;"><b>Opening remarks</b></td></tr>
+
<tr><td valign=top style="padding-top: 14px;"><b>9:00&#8211;9:15</b></td><td valign=top style="padding-top: 14px;"><b>Opening remarks</b></td></tr>
<tr><td valign=top style="padding-top: 14px;"><b>9:10&#8211;10:30</b></td><td valign=top style="padding-top: 14px;"><b>Session 1: Clinical NLP</b></td></tr>
+
<tr><td valign=top style="padding-top: 14px;"><b>9:15&#8211;10:30</b></td><td valign=top style="padding-top: 14px;"><b>Session 1: Clinical NLP</b></td></tr>
<tr><td valign=top width=100>9:10&#8211;9:30</td><td valign=top align=left><i>Embedding Transfer for Low-Resource Medical Named Entity Recognition: A Case Study on Patient Mobility</i><br>
+
<tr><td valign=top width=100>9:15&#8211;9:30</td><td valign=top align=left><i>Embedding Transfer for Low-Resource Medical Named Entity Recognition: A Case Study on Patient Mobility</i>><br>
 
Denis Newman-Griffis and Ayah Zirikly</td></tr>
 
Denis Newman-Griffis and Ayah Zirikly</td></tr>
<tr><td valign=top width=100>9:30&#8211;9:50</td><td valign=top align=left><i>Multi-task learning for interpretable cause of death classification using key phrase prediction</i><br>
+
<tr><td valign=top width=100>9:30&#8211;9:45</td><td valign=top align=left><i>Multi-task learning for interpretable cause of death classification using key phrase prediction</i><br>
 
Serena Jeblee, Mireille Gomes and Graeme Hirst</td></tr>
 
Serena Jeblee, Mireille Gomes and Graeme Hirst</td></tr>
<tr><td valign=top width=100>9:50&#8211;10:10</td><td valign=top align=left><i>Identifying Risk Factors For Heart Disease in Electronic Medical Records: A Deep Learning Approach</i><br>
+
<tr><td valign=top width=100>9:45&#8211;10:00</td><td valign=top align=left><i>Identifying Risk Factors For Heart Disease in Electronic Medical Records: A Deep Learning Approach</i><br>
 
Thanat Chokwijitkul, Anthony Nguyen, Hamed Hassanzadeh and Siegfried Perez</td></tr>
 
Thanat Chokwijitkul, Anthony Nguyen, Hamed Hassanzadeh and Siegfried Perez</td></tr>
<tr><td valign=top width=100>10:10&#8211;10:30</td><td valign=top align=left><i>Identifying Key Sentences for Precision Oncology Using Semi-Supervised Learning</i><br>
+
<tr><td valign=top width=100>10:00&#8211;10:15</td><td valign=top align=left><i>Keyphrases Extraction from User-Generated Contents in Healthcare Domain Using Long Short-Term Memory Networks</i><br>
 +
Ilham Fathy Saputra, Rahmad Mahendra and Alfan Farizki Wicaksono</td></tr>
 +
<tr><td valign=top width=100>10:15&#8211;10:30</td><td valign=top align=left><i>Identifying Key Sentences for Precision Oncology Using Semi-Supervised Learning</i><br>
 
Jurica &#352;eva, Martin Wackerbauer and Ulf Leser</td></tr>
 
Jurica &#352;eva, Martin Wackerbauer and Ulf Leser</td></tr>
 
<tr><td valign=top style="padding-top: 14px;"><b>10:30&#8211;11:00</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;"><b>10:30&#8211;11:00</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;"><b>11:00&#8211;12:30</b></td><td valign=top style="padding-top: 14px;"><b>Session 2: Foundations</b></td></tr>
 
<tr><td valign=top style="padding-top: 14px;"><b>11:00&#8211;12:30</b></td><td valign=top style="padding-top: 14px;"><b>Session 2: Foundations</b></td></tr>
<tr><td valign=top width=100>11:00&#8211;11:20</td><td valign=top align=left><i>Ontology alignment in the biomedical domain using entity definitions and context</i><br>
+
<tr><td valign=top width=100>11:00&#8211;11:15</td><td valign=top align=left><i>Ontology alignment in the biomedical domain using entity definitions and context</i><br>
 
Lucy Wang, Chandra Bhagavatula, Mark Neumann, Kyle Lo, Chris Wilhelm and Waleed Ammar</td></tr>
 
Lucy Wang, Chandra Bhagavatula, Mark Neumann, Kyle Lo, Chris Wilhelm and Waleed Ammar</td></tr>
<tr><td valign=top width=100>11:20&#8211;11:40</td><td valign=top align=left><i>Sub-word information in pre-trained biomedical word representations: evaluation and hyper-parameter optimization</i><br>
+
<tr><td valign=top width=100>11:15&#8211;11:30</td><td valign=top align=left><i>Sub-word information in pre-trained biomedical word representations: evaluation and hyper-parameter optimization</i><br>
 
Dieter Galea, Ivan Laponogov and Kirill Veselkov</td></tr>
 
Dieter Galea, Ivan Laponogov and Kirill Veselkov</td></tr>
<tr><td valign=top width=100>11:40&#8211;12:00</td><td valign=top align=left><i>Keyphrases Extraction from User-Generated Contents in Healthcare Domain Using Long Short-Term Memory Networks</i><br>
+
<tr><td valign=top width=100>11:30&#8211;11:45</td><td valign=top align=left><i>PICO Element Detection in Medical Text via Long Short-Term Memory Neural Networks</i><br>
Ilham Fathy Saputra, Rahmad Mahendra and Alfan Farizki Wicaksono</td></tr>
+
Di Jin and Peter Szolovits</td></tr>
<tr><td valign=top width=100>12:00&#8211;12:20</td><td valign=top align=left><i>Coding Structures and Actions with the COSTA Scheme in Medical Conversations</i><br>
+
<tr><td valign=top width=100>11:45&#8211;12:00</td><td valign=top align=left><i>Coding Structures and Actions with the COSTA Scheme in Medical Conversations</i><br>
 
Nan Wang, Yan Song and Fei Xia</td></tr>
 
Nan Wang, Yan Song and Fei Xia</td></tr>
<tr><td valign=top style="padding-top: 14px;"><b>12:30&#8211;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;"><b>12:00&#8211;13:30</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;"><b>14:00&#8211;15:00</b></td><td valign=top style="padding-top: 14px;"><b>Invited Talk: "Automating systematic reviews: progress and challenges" &#8211; Paul Glasziou</b></td></tr>
+
<tr><td valign=top style="padding-top: 14px;"><b>13:30&#8211;14:30</b></td><td valign=top style="padding-top: 14px;"><b>Invited Talk: "Automating systematic reviews: progress and challenges" &#8211; Paul Glasziou</b></td></tr>
<tr><td valign=top style="padding-top: 14px;"><b>15:00&#8211;15:30</b></td><td valign=top style="padding-top: 14px;"><b>Invited Presentation: "A Corpus with Multi-Level Annotations of Patients, Interventions and Outcomes to Support Language Processing for Medical Literature" &#8211; Ben Nye</b></td></tr>
+
<tr><td valign=top style="padding-top: 14px;"><b>14:30&#8211;15:30</b></td><td valign=top style="padding-top: 14px;"><b>Session 3 Literature mining and retrieval; Question Answering</b></td></tr>
<tr><td valign=top style="padding-top: 14px;"><b>15:30&#8211;16:00</b></td><td valign=top style="padding-top: 14px;"><b><em>Coffee Break</em></b></td></tr>
+
<tr><td valign=top width=100>14:30&#8211;14:45</td><td valign=top align=left><i>A Neural Autoencoder Approach for Document Ranking and Query Refinement in Pharmacogenomic Information Retrieval</i><br>
<tr><td valign=top style="padding-top: 14px;"><b>16:00&#8211;16:30</b></td><td valign=top style="padding-top: 14px;"><b>Session 3 Literature mining and retrieval; Question Answering</b></td></tr>
 
<tr><td valign=top width=100>16:00&#8211;16:20</td><td valign=top align=left><i>A Neural Autoencoder Approach for Document Ranking and Query Refinement in Pharmacogenomic Information Retrieval</i><br>
 
 
Jonas Pfeiffer, Samuel Broscheit, Rainer Gemulla and Mathias G&ouml;schl</td></tr>
 
Jonas Pfeiffer, Samuel Broscheit, Rainer Gemulla and Mathias G&ouml;schl</td></tr>
<tr><td valign=top width=100>16:20&#8211;16:40</td><td valign=top align=left><i>Biomedical Event Extraction Using Convolutional Neural Networks and Dependency Parsing</i><br>
+
<tr><td valign=top width=100>14:45&#8211;15:00</td><td valign=top align=left><i>Biomedical Event Extraction Using Convolutional Neural Networks and Dependency Parsing</i><br>
 
Jari Bj&ouml;rne and Tapio Salakoski</td></tr>
 
Jari Bj&ouml;rne and Tapio Salakoski</td></tr>
<tr><td valign=top width=100>16:40&#8211;17:00</td><td valign=top align=left><i>BioAMA: Towards an End to End BioMedical Question Answering System</i><br>
+
<tr><td valign=top width=100>15:00&#8211;15:15</td><td valign=top align=left><i>BioAMA: Towards an End to End BioMedical Question Answering System</i><br>
 
Vasu Sharma, Nitish Kulkarni, Srividya Pranavi, Gabriel Bayomi, Eric Nyberg and Teruko Mitamura</td></tr>
 
Vasu Sharma, Nitish Kulkarni, Srividya Pranavi, Gabriel Bayomi, Eric Nyberg and Teruko Mitamura</td></tr>
<tr><td valign=top width=100>17:00&#8211;17:20</td><td valign=top align=left><i>Phrase2VecGLM: Neural generalized language model&#8211;based semantic tagging for complex query reformulation in medical IR</i><br>
+
<tr><td valign=top width=100>15:15&#8211;15:30</td><td valign=top align=left><i>Phrase2VecGLM: Neural generalized language model&#8211;based semantic tagging for complex query reformulation in medical IR</i><br>
 
Manirupa Das, Eric Fosler-Lussier, Simon Lin, Soheil Moosavinasab, David Chen, Steve Rust, Yungui Huang and Rajiv Ramnath</td></tr>
 
Manirupa Das, Eric Fosler-Lussier, Simon Lin, Soheil Moosavinasab, David Chen, Steve Rust, Yungui Huang and Rajiv Ramnath</td></tr>
<tr><td valign=top width=100>17:20&#8211;17:40</td><td valign=top align=left><i>PICO Element Detection in Medical Text via Long Short-Term Memory Neural Networks</i><br>
+
<tr><td valign=top style="padding-top: 14px;"><b>15:30&#8211;16:00</b></td><td valign=top style="padding-top: 14px;"><b><em>Coffee Break</em></b></td></tr>
Di Jin and Peter Szolovits</td></tr>
+
<tr><td valign=top style="padding-top: 14px;"><b>16:00&#8211;16:15</b></td><td valign=top style="padding-top: 14px;"><b>Invited Presentation: "A Corpus with Multi-Level Annotations of Patients, Interventions and Outcomes to Support Language Processing for Medical Literature" &#8211; Ben Nye</b></td></tr>
<tr><td valign=top style="padding-top: 14px;"><b>17:40&#8211;18:00</b></td><td valign=top style="padding-top: 14px;"><b>Poster Session</b></td></tr>
+
<tr><td valign=top style="padding-top: 14px;"><b>16:15&#8211;18:00</b></td><td valign=top style="padding-top: 14px;"><b>Poster Session</b></td></tr>
 
<tr><td valign=top width=100>&nbsp;</td><td valign=top align=left><i>Convolutional neural networks for chemical-disease relation extraction are improved with character-based word embeddings</i><br>
 
<tr><td valign=top width=100>&nbsp;</td><td valign=top align=left><i>Convolutional neural networks for chemical-disease relation extraction are improved with character-based word embeddings</i><br>
 
Dat Quoc Nguyen and Karin Verspoor</td></tr>
 
Dat Quoc Nguyen and Karin Verspoor</td></tr>
Line 79: Line 77:
 
<tr><td valign=top width=100>&nbsp;</td><td valign=top align=left><i>Toward Cross-Domain Engagement Analysis in Medical Notes</i><br>
 
<tr><td valign=top width=100>&nbsp;</td><td valign=top align=left><i>Toward Cross-Domain Engagement Analysis in Medical Notes</i><br>
 
Sara Rosenthal and Adam Faulkner</td></tr>
 
Sara Rosenthal and Adam Faulkner</td></tr>
</table></center><p>
+
</table>
  
  

Revision as of 13:02, 10 June 2018

SIGBIOMED

BIONLP 2018

An ACL 2018 Workshop associated with the SIGBIOMED special interest group, Melbourne, Australia, Thursday July 19, 2018


IMPORTANT DATES

  • Submission deadline: Monday April 16, 2018 11:59 PM Eastern US
  • Notification of acceptance: Monday May 21, Thursday, May 24, 2018 (Sorry for the delay)
  • Camera-ready copy due from authors: Monday May 28, Thursday, May 31, 2018
  • Workshop: Thursday July 19, 2018


BioNLP 2018 WORKSHOP PROGRAM

Thursday July 19, 2018
9:00–9:15Opening remarks
9:15–10:30Session 1: Clinical NLP
9:15–9:30Embedding Transfer for Low-Resource Medical Named Entity Recognition: A Case Study on Patient Mobility>
Denis Newman-Griffis and Ayah Zirikly
9:30–9:45Multi-task learning for interpretable cause of death classification using key phrase prediction
Serena Jeblee, Mireille Gomes and Graeme Hirst
9:45–10:00Identifying Risk Factors For Heart Disease in Electronic Medical Records: A Deep Learning Approach
Thanat Chokwijitkul, Anthony Nguyen, Hamed Hassanzadeh and Siegfried Perez
10:00–10:15Keyphrases Extraction from User-Generated Contents in Healthcare Domain Using Long Short-Term Memory Networks
Ilham Fathy Saputra, Rahmad Mahendra and Alfan Farizki Wicaksono
10:15–10:30Identifying Key Sentences for Precision Oncology Using Semi-Supervised Learning
Jurica Ševa, Martin Wackerbauer and Ulf Leser
10:30–11:00Coffee Break
11:00–12:30Session 2: Foundations
11:00–11:15Ontology alignment in the biomedical domain using entity definitions and context
Lucy Wang, Chandra Bhagavatula, Mark Neumann, Kyle Lo, Chris Wilhelm and Waleed Ammar
11:15–11:30Sub-word information in pre-trained biomedical word representations: evaluation and hyper-parameter optimization
Dieter Galea, Ivan Laponogov and Kirill Veselkov
11:30–11:45PICO Element Detection in Medical Text via Long Short-Term Memory Neural Networks
Di Jin and Peter Szolovits
11:45–12:00Coding Structures and Actions with the COSTA Scheme in Medical Conversations
Nan Wang, Yan Song and Fei Xia
12:00–13:30Lunch break
13:30–14:30Invited Talk: "Automating systematic reviews: progress and challenges" – Paul Glasziou
14:30–15:30Session 3 Literature mining and retrieval; Question Answering
14:30–14:45A Neural Autoencoder Approach for Document Ranking and Query Refinement in Pharmacogenomic Information Retrieval
Jonas Pfeiffer, Samuel Broscheit, Rainer Gemulla and Mathias Göschl
14:45–15:00Biomedical Event Extraction Using Convolutional Neural Networks and Dependency Parsing
Jari Björne and Tapio Salakoski
15:00–15:15BioAMA: Towards an End to End BioMedical Question Answering System
Vasu Sharma, Nitish Kulkarni, Srividya Pranavi, Gabriel Bayomi, Eric Nyberg and Teruko Mitamura
15:15–15:30Phrase2VecGLM: Neural generalized language model–based semantic tagging for complex query reformulation in medical IR
Manirupa Das, Eric Fosler-Lussier, Simon Lin, Soheil Moosavinasab, David Chen, Steve Rust, Yungui Huang and Rajiv Ramnath
15:30–16:00Coffee Break
16:00–16:15Invited Presentation: "A Corpus with Multi-Level Annotations of Patients, Interventions and Outcomes to Support Language Processing for Medical Literature" – Ben Nye
16:15–18:00Poster Session
 Convolutional neural networks for chemical-disease relation extraction are improved with character-based word embeddings
Dat Quoc Nguyen and Karin Verspoor
 Domain Adaptation for Disease Phrase Matching with Adversarial Networks
Miaofeng Liu, Jialong Han, Haisong Zhang and Yan Song
 Predicting Discharge Disposition Using Patient Complaint Notes in Electronic Medical Records
Mohamad Salimi and Alla Rozovskaya
 Bacteria and Biotope Entity Recognition Using A Dictionary-Enhanced Neural Network Model
Qiuyue Wang and Xiaofeng Meng
 SingleCite: Towards an improved Single Citation Search in PubMed
Lana Yeganova, Donald C Comeau, Won Kim, W John Wilbur and Zhiyong Lu
 A Framework for Developing and Evaluating Word Embeddings of Drug-named Entity
Mengnan Zhao, Aaron J. Masino and Christopher C. Yang
 MeSH-based dataset for measuring the relevance of text retrieval
Won Gyu KIM, Lana Yeganova, Donald comeau, W John Wilbur and Zhiyong Lu
 CRF-LSTM Text Mining Method Unveiling the Pharmacological Mechanism of Off-target Side Effect of Anti-Multiple Myeloma Drugs
Kaiyin Zhou, Sheng Zhang, Xiangyu Meng, Qi Luo, Yuxing Wang, Ke Ding, Yukun Feng, Mo Chen, Kevin Cohen and Jingbo Xia
 Prediction Models for Risk of Type-2 Diabetes Using Health Claims
Masatoshi Nagata, Kohichi Takai, Keiji Yasuda, Panikos Heracleous and Akio Yoneyama
 On Learning Better Embeddings from Chinese Clinical Records: Study on Combining In-Domain and Out-Domain Data
Yaqiang Wang, Yunhui Chen, Hongping Shu and Yongguang Jiang
 Investigating Domain-Specific Information for Neural Coreference Resolution on Biomedical Texts
Long Trieu, Nhung Nguyen, Makoto Miwa and Sophia Ananiadou
 Toward Cross-Domain Engagement Analysis in Medical Notes
Sara Rosenthal and Adam Faulkner


SUBMISSION INSTRUCTIONS

Two types of submissions are invited: full papers and short papers. Submissions are due by 11:59 PM EST on Monday April 16, 2018.

Full papers should not exceed eight (8) pages of text, plus unlimited references. These 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 four (4) content pages in the proceedings. Appropriate short paper topics include preliminary results, application notes, descriptions of work in progress, etc.

Electronic Submission
Submissions must be electronic and in PDF format, using the Softconf START conference management system at https://www.softconf.com/acl2018/BioNLP/

We strongly recommend consulting ACL new 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. Style files and other information about paper formatting requirements are available on the conference website, http://acl2018.org/call-for-papers/. Scroll down to “Paper Submission and Templates.”

Submissions need to be anonymous.

Dual submission policy: papers may NOT be submitted to the BioNLP 2018 workshop if they are or will be concurrently submitted to another meeting or publication.

KEYNOTE

Keynote presentation by Dr. Paul Glasziou [1]


WORKSHOP OVERVIEW AND SCOPE

Over the course of the past sixteen years, 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. This year we are expanding our interests, and in addition to the topics listed below, we welcome submissions on the lessons learned while reproducing published results.

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
  • Theoretical underpinnings of biomedical language processing
  • Research Reproducibility

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 
 * Olivier Bodenreider, US National Library of Medicine 
 * Leonardo Campillos Llanos, LIMSI - CNRS, France
 * Kevin Bretonnel Cohen, University of Colorado School of Medicine, USA 
 * Brian Connolly, Kroger Digital, USA
 * Dina Demner-Fushman, US National Library of Medicine 
 * Filip Ginter, University of Turku, Finland 
 * Cyril Grouin, LIMSI - CNRS, France 
 * Tudor Groza, The Garvan Institute of Medical Research, Australia
 * Graciela Gonzalez, University of Pennsylvania, USA
 * Travis Goodwin, The University of Texas at Dallas, USA
 * Antonio Jimeno Yepes, IBM, Melbourne Area, Australia
 * Halil Kilicoglu, US National Library of Medicine
 * Robert Leaman, US National Library of Medicine 
 * Ulf Leser, Humboldt-Universität zu Berlin, Germany 
 * Zhiyong Lu, US National Library of Medicine 
 * Timothy Miller, Children’s Hospital Boston, USA 
 * Makoto Miwa, Toyota Technological Institute, Japan 
 * 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, Hasso Plattner Institute and University of Potsdam, Germany
 * Nhung Nguyen, The University of Manchester, UK
 * Naoaki Okazaki, Tohoku University, Japan 
 * Sampo Pyysalo, University of Cambridge, UK 
 * Francisco J. Ribadas-Pena, University of Vigo, Spain
 * Fabio Rinaldi,  University of Zurich, Switzerland 
 * Kirk Roberts, The University of Texas Health Science Center at Houston, USA 
 * Angus Roberts, The University of Sheffield, UK 
 * Hagit Shatkay, University of Delaware, USA 
 * Pontus Stenetorp, University College London, UK
 * Karin Verspoor, The University of Melbourne, Australia 
 * Byron C. Wallace,  University of Texas at Austin, USA 
 * Jingbo Xia, Huazhong Agricultural University, China
 * 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