WWW 2014 - The World Wide Web and Public Health Intelligence

In the tightly interconnected world of the 21st century, infectious disease pandemics remain a constant threat to global health. At the same time, noncommunicable 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 nontraditional online resources such as social networks, blogs, news feed, twitter posts, and online communities due to their sheer size and dynamic structure.
Topics
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 (for example, 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.