Conferences

6 June 2018, Fort Worth, Texas, USA
2nd Workshop on Curative Power of MEdical DAta (MEDA 2018)

Organizing Committee:
Diana Trandabăț ("Alexandru Ioan Cuza" University of Iași, Romania)
Daniela Gîfu ("Alexandru Ioan Cuza" University of Iași, Romania Romanian Academy - Iaşi branch)
Kevin Cohen (Computational Bioscience Program U. Colorado School of Medicine)
Jingbo Xia (Huazhong Agricultural University, P.R. China)

In an era when massive amounts of medical data became available, researchers working in biological, biomedical and clinical domains have increasingly started to require the help of language engineers to process large quantities of biomedical and molecular biology literature (such as PubMed), patient data or health records. Linking the contents of these documents to each other, as well as to specialized ontologies, could enable access to and discovery of structured clinical information and foster a major leap in natural language processing and health research.
MEDA-2018 aims to gather innovative approaches for the exploitation of biomedical data using semantic web technologies and linked data by bringing together practitioners, researchers, and scholars to share examples, use cases, theories and analysis of biomedical data. The main objective of this second edition workshop is to consolidate an internationally appreciated forum for scientific research in BioMed, with emphasis on crowdsourcing, semantic web, knowledge integration and data linking.

The scientific program of MEDA-2018 will focus around the following topics:

Crowdsourcing approaches in biomedicine
Collaborative computational technologies for biomedical research
Biomedical digital libraries
Mining biomedical literature
Event-based text mining for biology and related fields
Event and entity extraction in medical texts
Conceptual graphs extracted from medical texts
Annotation of semantic content, with applications in medicine and biology
Techniques for Big Data in Healthcare
Medical search engines
Distributed communication system in biomedical applications
Deep learning for bioinformatics
Biomedical question/answering
Biomedical topic modeling
Biomedical language systems
Text summarization in the biomedical domain.

https://profs.info.uaic.ro/~meda/

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