27.3498, Confs: Comp Ling, Text/Corpus Ling/USA

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Tue Sep 6 14:34:54 EDT 2016


LINGUIST List: Vol-27-3498. Tue Sep 06 2016. ISSN: 1069 - 4875.

Subject: 27.3498, Confs: Comp Ling, Text/Corpus Ling/USA

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Date: Tue, 06 Sep 2016 14:34:39
From: Neil Smalheiser [neils at uic.edu]
Subject: Evidence Synthesis - Current Practices and Future Possibilities

 
Evidence Synthesis – Current Practices and Future Possi 

Date: 05-Oct-2016 - 05-Oct-2016 
Location: Chicago, IL, USA 
Contact: Neil Smalheiser 
Contact Email: neils at uic.edu 
Meeting URL: http://www.ieee-ichi.org/panel.html 

Linguistic Field(s): Computational Linguistics; Text/Corpus Linguistics 

Meeting Description: 

Panel Chair:

Neil R. Smalheiser, University of Illinois at Chicago, College of Medicine

Panelists:

Spyros Kitsiou, University of Illinois at Chicago, College of Medicine
Aaron M. Cohen, Oregon Health & Science University
Siddhartha Jonnalagadda, Microsoft
Byron Wallace, Northeastern University
Sophia Ananiadou, The University of Manchester, National Centre for Text
Mining

Oct 5 2016 1:30 pm – 5:00 pm

This session has two main goals. First, it is designed to inform new
investigators of the importance of automating evidence synthesis, and
emphasize the potential for new research in this area. Second, it provides an
opportunity for five of the leading laboratories across the US and UK to come
together, to review the current state of the art, and discuss in detail the
nuts-and-bolts of different technical approaches to overcoming the key
challenges of evidence synthesis.

Dr. Kitsiou will give an overview of the different types of literature reviews
and evidence synthesis approaches in health informatics, with emphasis on
systematic reviews and meta-analyses, for those not in the field: discussing
how they are generated, and the bottlenecks in generating them efficiently and
with adequate quality. Dr. Cohen will give an overview of the efforts by
laboratories worldwide to improve and automate the process of writing and
updating systematic reviews in evidence-based medicine. Dr. Smalheiser will
present his research in identifying relevant clinical trials to examine,
whereas Drs. Jonnalagadda, Wallace, and Ananiadou will discuss and compare
their approaches to extracting data from clinical trial articles. Finally,
there will be guided general discussion to consider the scope, limitations and
potential for text mining techniques to automate, streamline and re-engineer
the largely manual process of writing systematic reviews.
 






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