24 March 2014

The AAAI-14 International Workshop on the World Wide Web and Public Health Intelligence (W3PHI 2014)

The AAAI-14 International Workshop on the World Wide Web and Public Health Intelligence (W3PHI 2014)

In conjunction with the 28th AAAI Conference on Artificial Intelligence (AAAI-14) July 27–31, 2014 in Québec City, Québec, Canada

In the tightly interconnected world of the 21st century, infectious disease pandemics remain a constant threat to global health. At the same time, non-communicable diseases have become the main cause of global disability and death, imposing a crushing burden on societies and economies around the world. Public Health Intelligence obtained through intelligent knowledge exchange and real-time surveillance is increasingly recognized as a critical tool for promoting health, preventing disease, and triggering timely response to critical public health events such as disease outbreaks and acts of bioterrorism. This intelligence is created by increasingly sophisticated informatics platforms that collect and integrate data from multiple sources, and apply analytics to generate insights that will improve decision-making at individual and societal levels.

Driven by omnipresent threats to public health and the potential of public health intelligence, governments and researchers now collect data from many sources, and analyze these data together to estimate the incidence and prevalence of different health conditions, as well as related risk factors. Modern surveillance systems employ tools and techniques from artificial intelligence and machine learning to monitor direct and indirect signals and indicators of disease to enable early, automatic detection of emerging outbreaks and other health-relevant patterns. Given the ever-increasing role of the World Wide Web as a source of data for public health surveillance, accessing, managing, and analyzing its content has brought new opportunities and challenges; particularly for non-traditional online resources such as social networks, blogs, news feed, twitter posts, and online communities due to their sheer size and dynamic structure.

The workshop will include original contributions on theory, methods, systems, and applications of data mining, machine learning, databases, natural language processing, knowledge representation, artificial intelligence, semantic web, and big data analytics in web-based healthcare applications, with a focus on applications in public health. The scope of the workshop includes, but is not limited to, the following areas:
  • Geographical Mapping and Visual analytics for Health Data
  • Social Media Analytics
  • Epidemic Intelligence
  • Predictive modelling and Decision support
  • Biomedical Ontologies, terminologies and standards
  • Bayesian Networks and Reasoning under Uncertainty
  • Temporal and Spatial Representation and Reasoning
  • Case-based Reasoning in Healthcare
  • Crowdsourcing, and Collective Intelligence
  • Risk assessment, Trust, Ethics, and Privacy
  • Sentiment Analysis and Opinion Mining
  • Computational Behavioral/Cognitive Modeling
Applications in Epidemiology and Surveillance (e.g. Bioterrorism, Participatory Surveillance)
This workshop aims to bring together a wide range of computer scientists, biomedical and health informaticians, researchers, students, industry professionals, representatives of national and international public health agencies, and NGOs interested in the theory and practice of computational models of web-based public health intelligence to highlight the latest achievements in epidemiological surveillance based on monitoring online communications and interactions on the World Wide Web. The workshop will promote open debate and exchange of opinions among participants.

The workshop will consist of welcome session, keynote and invited talks, full/short paper presentations, demos, posters, and a panel discussion.

Submission requirements
We invite researchers and industrial practitioners to submit their original contributions following AAAI format through EasyChair. Three categories of contribution are sought: full-research papers up to 8 pages; short paper up to 4 pages; and posters and demos up to 2 pages.

All accepted papers will appear in the AAAI 2014 Workshops Proceedings. We will tentatively invite the best submissions to extend their papers in order to be published in a special issue of a journal. Also the post-workshop proceedings including the extended/revised versions of selected papers will be published in Lecture Notes in Social Networks (Springer).

Important Dates
- Paper submission deadlines: April 10, 2014- Notification of Acceptance: May 1, 2014- Final camera-ready copy hard deadline: May 15, 2014 - Workshop: 27 or 28 July 2014

Workshop Chairs
David L. Buckeridge, MD, PhD,
McGill Clinical & Health Informatics, McGill University
1140 Pine Avenue West,
Montreal, Quebec, H3A 1A3 CANADA, (514) 398-8355 (tel)

(514) 843-1551 (fax)
Email: david.buckeridge@mcgill.ca Url:
Arash Shaban-Nejad, PhD,
McGill Clinical & Health Informatics, McGill University
1140 Pine Avenue West,
Montreal, Quebec, H3A 1A3 CANADA, (514) 934-1934 ext. 32986 (tel)

(514) 843-1551 (fax)
Email: arash.shaban-nejad@mcgill.ca Url:
John S. Brownstein, PhD
Boston Children's Hospital, Harvard University, Autumn St, Room 451, Boston, MA 02215 USA, (617) 355-6998 (tel)
(617) 730-0921 (fax)
Email: john_brownstein@harvard.edu Url:

Workshop Scientific Committee:
Mark Musen, Stanford University, USA (musen@stanford.edu)
Nigam Shah, Stanford University, USA (
Senjuti Basu Roy, University of Washington, Tacoma, USA (
Nigel Collier, National Institute of Informatics, Japan (
David L. Buckeridge, McGill University, Canada (
Ciro Cattuto, ISI Foundation, Turin, Italy (
Maged Kamel Boulos, University of Plymouth, UK (
maged.kamelboulos@plymouth.ac.uk) John S. Brownstein, Harvard University, USA (http://chip.org/john-brownstein)
Masoumeh T. Izadi, McGill University, Canada (
Jiang Guoqian, Mayo Clinic, Rochester, USA (
Neil F. Abernethy, University of Washington, USA (
Chris Paton, University of Oxford, UK (
Christopher J.O. Baker, University of New Brunswick (
Alessio Signorini, University of Iowa, USA (
Arash Shaban-Nejad, McGill University, Canada (
Jason J. Jung, Yeungnam University, Republic of Korea (
Courtney D. Corley, Pacific Northwest National Lab, USA (
Ameen Abu-Hanna, University of Amsterdam, Netherlands (
a.abu-hanna@amc.uva.nl) Anette Hulth, Karolinska Institute, Sweden (anette.hulth@smi.se)
Trevor Cohen, University of Texas Health Science, USA (
Trevor.Cohen@uth.tmc.edu) Mark Dredze, Johns Hopkins University, USA (mdredze@cs.jhu.edu)
Noémie Elhadad, Columbia University, USA (

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