Social data and medical data analytics special track

IEEE Computer-Based Medical Systems 2018 (CBMS 2018)

Karlstad University, Karlstad, Sweden, June 18-21, 2018

Call for papers (download PDF version)

Special Track on Social data and medical data analytics

The growing availability and accessibility of key health-related data resources and the rapid proliferation of technological developments in data analytics is helping to extract the power of these datasets to improve diagnosis, shorten the time to market of drugs, help in early outbreak detection, improve education of healthcare professionals and reduce costs to name but a few.

Extracting the knowledge to make this a reality is still a daunting task: on the one hand, data sources are not integrated, they contain private information and are not structured. On the other hand, we still lack context- and privacy-aware algorithms to extract the knowledge after a proper curation and enrichment of the datasets.

Technology in recent years has made it possible not only to get data from the healthcare environment (hospitals, health centres, laboratories, etc.). It also allows information to be obtained from society itself (sensors, monitoring, Internet of Things (IoT) devices, social networks, etc.). In particular, social environments are a new source of data that allows information to be obtained at all community levels.

Health environments would benefit directly through the acquisition and the analysis of the information generated in any kind of social environment such as social networks, forums, chats, social sensors, Internet of Things (IoT) devices, surveillance systems, virtual worlds, to name but a few. These environments provides an incredible and rich amount of information that could be analysed and applied to the benefit of public health allowing the quality of life of the population to be improved as well as reducing economic costs. Policymakers, researchers, health professionals and managers are still attempting, with no great success, to acquire health information upon which to base their decisions.

The topics to be covered include the design, development, evaluation or validation of computer-based medical systems or methods within the following (but not limited to) areas: