Summer School on “Biomedical Text Processing”
13th in the series of Eurolan Schools
Biomedical Text Mining (BioNLP) applies natural language processing (NLP) techniques to identify and extract information from scientific publications in biology, medicine, and chemistry, in order to discover novel knowledge that can contribute to biomedical research. The large size of the biomedical literature and its rapid growth in recent years make literature search and information access a demanding task. Health-care professionals in the clinical domain face a similar problem of information explosion when dealing with the ever-increasing body of available medical/health records in electronic form. Overall, the application of automatic NLP techniques to unstructured text in scientific literature and medical records enables life scientists to find and exploit this data.
EUROLAN-2017 has engaged several well-known researchers in the fields of BioNLP and NLP to provide a comprehensive overview of language processing models and techniques applicable to the biomedical domain, ranging from an introduction to fundamental NLP technologies to the study of use cases and exploitation of available tools and frameworks that support BioNLP. Tutorial are accompanied by hands-on sessions.
The goal of EUROLAN 2017 is to insert into the participants’ minds information on the theory, methodology, and technology of processing biological, biomedical and clinical data. Experienced brainwashers will spend all mornings trying to convince you, and all afternoons trying to test the effect of their previous efforts. In translation, tutorials on a variety of topics will be accompanied with hands-on sessions on using textual data mining tools on a variety of biomedical type.
In case you are wondering what will really happen, the list of main topics should give you an idea:
- mining biomedical literature
- mining biomedical literature
- event-based text mining for biology and related fields
- event extraction in medical texts
- entity identification and normalization
- conceptual graphs extracted from medical texts
- annotation of semantic content, with applications in medicine and biology
- textual big data techniques
- medical search engines
- HIT (health information technologies) and LT
- deep learning for bioinformatics
- biomedical question/aswering (see also the BioASQ evaluation challenge)
- Clinical Data Repositories / Big Data and Cloud Computing
- clinical relationships
- medical topic modeling
- medical language systems
- clinical text analysis
- text summarization in the biomedical domain
Mihaela Breabăn – “Alexandru Ioan Cuza” University of Iași (Romania)
Kevin Cohen – University of Colorado School of Medicine (USA) and LIMSI, CNRS, Université Paris-Saclay, Orsay (France)
Noa Patricia Cruz Diaz – Virgen del Rocio University Hospital (Spain)
Eric Gaussier – University Grenoble Alps (France)
Nancy Ide – Vassar College (USA)
Pierre Zweigenbaum – LIMSI, CNRS, Université Paris-Saclay, Orsay (France)
• Romanian Academy
• “Alexandru Ioan Cuza” University of Iași
• “Ovidius” University of Constanța
• Vassar College
• Technical Sciences Academy of Romania
• Romanian Association of Computational Linguistics
EUROLAN-2017 is hosted by the “Ovidius” University of Constanța, Faculty of Mathematics and Computer Science and Faculty of Medicine, in Constanța, Romania.
Low-cost accommodation for EUROLAN students is available in the University’s hostel (shared double rooms). Alternatively, participants may opt for a number of hotels in the city of Constanța or Mamaia.
REGISTRATION AND FEES:
Before 18 August: 400 EUR (extended)
19 August and later: 450 EUR (adjusted)
These fees are applicable only to students; for other types of participants, see http://eurolan.info.uaic.ro/2017/information.html.