Project Details
National Support for Project Medical Ecosystem - Personalized Event-based Surveillance
Project Period: 1. 1. 2010 – 30. 6. 2012
Project Type: grant
Code: 7E10054
Agency: Ministerstvo školství, mládeže a tělovýchovy ČR
Program: Podpora projektů sedmého rámcového programu Evropského společenství pro výzkum, technologický rozvoj a demonstrace (2007 až 2013) podle zákona č. 171/2007 Sb.
Public Health Event Detection, Personalization, User
Generated
Content
Many factors in today’s changing societies contribute towards the
continuous emergence of infectious diseases.
Demographic change,
globalization, bioterrorism, compounded with the resilient nature of
viruses and diseases
such as SARS and avian influenza have raised
awareness for European society’s increasing vulnerability.
Traditional
Epidemic Intelligence systems are designed to identify potential health
threats, and rely upon data
transmissions from laboratories or
hospitals. They can be used to recognise long-term trends, but are
limited
in several ways. Threats, such as SARS, can go unrecognised
since the signals indicating its existence may
originate from sources
other than the traditional ones. Second, a critical strategy for
circumventing devastating
public health events is early detection and
early response. Conflictingly, the time with which information
propagates
through the traditional channels, can undermine time-sensitive
strategies. Finally, traditional systems
are well suited for
recognising indicators for known diseases, but are not well designed for
detecting those
that are emerging. Faced with these limitations,
traditional systems need to be complemented with additional
approaches
which are better targeted for the early detection of emerging threats.
The
Medical EcoSystem (M-Eco) project, will address these limitations by
using Open Access Media and
User Generated Content, as unofficial
information sources for Epidemic Intelligence. This type of content has
transformed
the manner in which information propagates across the globe. Based on
this, M-Eco will develop
an Event-Based Epidemic Intelligence System
which integrates unofficial and traditional sources for the early
detection
of emerging health threats. M-Eco will emphasize adaptivity and
personalized filtering so that relevant
signals can be detected for
targeting the needs of public health officials who have to synthesize
facts, assess
risks and react to public health threats.
2013
- DENECKE, K.; KRIECK, M.; OTRUSINA, L.; SMRŽ, P.; DOLOG, P.; NEJDL, W.; VELASCO, E. How to Exploit Twitter for Public Health Monitoring. Methods of Information in Medicine, 2013, vol. 52, no. 4,
p. 326-339. ISSN: 0026-1270. Detail
2012
- OTRUSINA, L.; SMRŽ, P.; BACKFRIED, G. M-Eco D3.3 - M-Eco Media Content Analysis. Hannover: The Information Society Technologies (IST) 7th Framework programme, 2012.
p. 0-0. Detail - SMRŽ, P.; DENECKE, K.; DOLOG, P. Making use of social media data in public health. Proceedings of the 21st international conference companion on World Wide Web. New York: Association for Computing Machinery, 2012.
p. 243-246. ISBN: 978-1-4503-1230-1. Detail
2011
- DENECKE, K.; KIRCHNER, G.; DOLOG, P.; SMRŽ, P.; LINGE, J.; BACKFRIED, G.; DREESMAN, J. Event-Driven Architecture for Health Event Detection from Multiple Sources. Proceedings of the XXIII International Conference of the European Federation for Medical Informatics (MIE 2011). Oslo: IOS Press, 2011.
p. 160-164. ISBN: 978-1-60750-805-2. Detail - OTRUSINA, L.; DENECKE, K.; DREESMAN, J.; KRIECK, M. A New Age of Public Health: Identifying Disease Outbreaks by Analyzing Tweets. Proceedings of Health WebScience Workshop, ACM Web Science Conference. Koblenz: Association for Computing Machinery, 2011.
p. 10-15. Detail - OTRUSINA, L.; DREESMAN, J.; ECKMANNS, T.; KRIECK, M.; LINGE, J.; VELASCO, E. Social media and epidemiology: Tweets indicate Norovirus outbreak at a university. Proceedings of the European Congress of Clinical Microbiology and Infectious Diseases (ECCMID 2011). Milan: The European Society of Clinical Microbiology and Infectious Diseases, 2011.
p. 1-9. Detail - OTRUSINA, L.; DREESMAN, J.; ECKMANNS, T.; KRIECK, M.; LINGE, J.; VELASCO, E. Social media and epidemiology: Tweets indicate Norovirus outbreak at a university. Proceedings of the International Meeting on Emerging Diseases and Surveillance (IMED 2011). Brookline: International Society for Infectious Diseases, 2011.
p. 1-9. Detail - OTRUSINA, L.; SMRŽ, P. Finding Indicators of Epidemiological Events by Analyzing Messages from Twitter and Other Social Media. 20th ACM Conference on Information and Knowledge Management workshop proceedings by ACM. Glasgow: Association for Computing Machinery, 2011.
p. 1-4. ISBN: 978-1-4503-0950-9. Detail - OTRUSINA, L.; SMRŽ, P. M-Eco D3.2 - Semantic Annotator. Hannover: The Information Society Technologies (IST) 7th Framework programme, 2011.
s. 0-0. Detail
2010
- OTRUSINA, L.; SMRŽ, P. A New Approach to Pseudoword Generation. Proceedings of the Seventh conference on International Language Resources and Evaluation (LREC'10). Valletta: European Language Resources Association, 2010.
p. 1-5. ISBN: 2-9517408-6-7. Detail - OTRUSINA, L.; SMRŽ, P.; BACKFRIED, G. M-Eco D3.1 - Speech Recognition and Content Classification Subsystems. Hannover: Information and Communication Technologies (ICT) 7th Framework programme, 2010.
p. 0-0. Detail