<div dir="ltr"><span class="">First</span> <span class="">call</span> for Papers: Journal of Biomedical Informatics <span class="">Special</span>
<span class="">Issue</span> on Mining the Pharmacovigilance Literature<br>
Guest Editors: Isabel Segura-Bedmar, Paloma Martínez<br>
Computer Science Department<br>
Universidad Carlos III de Madrid, Spain<br>
<br>
<br>
<br>
We are pleased to announce a <span class="">Special</span> <span class="">Issue</span> of the Journal of
Biomedical Informatics on Mining the Pharmacovigilance Literature.
For detailed information, please see
<a href="http://www.journals.elsevier.com/journal-of-biomedical-informatics/call-for-papers/special-issue-on-mining-the-pharmacovigilance-literature/" target="_blank">http://www.journals.elsevier.com/journal-of-biomedical-informatics/<span class="">call</span>-for-papers/<span class="">special</span>-<span class="">issue</span>-on-mining-the-pharmacovigilance-literature/</a>.<br>
<br>
Pharmacovigilance is formally defined by WHO as ‘‘the science and
activities related to the detection, assessment, understanding and
prevention of adverse effects or any other drug-related problems’’.
Text Mining applied to the pharmacovigilance literature can be of
great benefit in the pharmaceutical industry, allowing
identification and extraction of relevant information, and providing
an interesting way to reduce the time spent by healthcare
professionals and researchers who are trying to stay current by
reviewing the literature.<br>
<br>
We encourage you to submit your articles for this <span class="">special</span> <span class="">issue</span> on
automatic extraction of relationships between biomedical entities
relevant to the Pharmacovigilance field. More specifically, we are
interested in papers that present new and novel approaches for the
extraction of drug–drug interactions (DDI) and drug side-effects
relationships from biomedical texts.<br>
<br>
We particularly welcome submissions that use the DDI corpus
(<a href="http://labda.inf.uc3m.es/ddicorpus" target="_blank">http://labda.inf.uc3m.es/ddicorpus</a>) because their results can be
compared with those reported in DDIExtraction 2013
(<a href="http://www.cs.york.ac.uk/semeval-2013/task9/" target="_blank">http://www.cs.york.ac.uk/semeval-2013/task9/</a>). In order to advance
in the extraction of drug–side effects relationships, we also
welcome contributions on the creation of gold standard corpora
annotated with drug–side effects.<br>
<br>
Topics of interest for submission to this <span class="">special</span> <span class="">issue</span> include (but
are not limited to):<br>
• Corpus development for pharmacovigilance text mining.<br>
• Named entity recognition for pharmacological substances and
side effects.<br>
• Relation extraction between drugs, particularly DDIs.<br>
• Relation extraction between drugs and side effects.<br>
• The creation and use of ontologies to represent knowledge
relevant to drug interactions and adverse drug effects.<br>
• The use of biomedical ontologies in combination with text
mining to facilitate the detection of Adverse Drug Reactions (ADRs)
and DDIs.<br>
• Review of the state of the art in text mining for
pharmacovigilance.<br>
<br>
<br>
Submission deadline: <b>September 30, 2014</b><br>
<br>
All submitted papers must be original and will undergo a rigorous
peer-review process with at least two reviewers. All submissions
should follow the guidelines for authors, available at the Journal
of Biomedical Informatics web site (<a href="http://www.journals.elsevier.com/journal-of-biomedical-informatics" target="_blank">http://www.journals.elsevier.com/journal-of-biomedical-informatics</a>).<br>
<br>
Authors must submit their paper by September 30, 2014 via the online
Elsevier Editorial System (EES) at <a href="http://ees.elsevier.com/jbi" target="_blank">http://ees.elsevier.com/jbi</a>.<br>
<br>
Please feel free to contact us if you need any further information.<br>
<br>
With our best regards,<br>
<br>
Isabel Segura-Bedmar and Paloma Martínez<br>
<br clear="all"><br>-- <br><div dir="ltr">Isabel Segura Bedmar<br>Profesor Visitante<br>Despacho 2.1.C.15, Telf: 91 624 59 61<br>Departamento de Informática, Universidad Carlos III de Madrid,<div>Laboratory for Advanced Database (LABDA)</div>
<div><a href="http://labda.inf.uc3m.es/doku.php?id=en:inicio" target="_blank">http://labda.inf.uc3m.es/doku.php?id=en:inicio</a></div><div><br></div></div>
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