Computer-based medical systems are facing a new challenge, created by
the rapid growth in information science and technology in general and
the complexity and volume of data in particular. Medical settings are
using sensors and networks of health information systems to integrate
data from patients, which requires storage, processing and management
operators to enable further analysis and knowledge discovery. The main
issue is that this data production often takes the form of high-speed
continuous flows of data, i.e. data streams.

Many applied computing researchers coming from different areas (data
mining, machine learning, intelligent data analysis, pattern
recognition, fuzzy logic, databases, etc.) are designing new
approaches or adapting some of the traditional algorithms to data
streams. On the other side, many physicians are addressing the need to
integrate streaming medical data into decision support systems.
	  
Dealing with continuous, and possibly infinite, flows of data require
different approaches for data processing and
management. Particular issues to address include summarization
of infinite data, resource-awareness, real-time monitoring of
changes and recurrences, etc. This is an incremental task that
requires incremental algorithms that integrate very large data
bases in medical domains. Streaming data is increasingly
important in the research community, as new algorithms are
needed to process medical data in reasonable time.
	  
Furthermore, medical domains introduce extra peculiarities to the
problem. For example, health information systems now deal with
heterogeneous data sources, possibly distributed across
healthcare institutions. Moreover, this data integration
requirement yields possibly privacy-preserving issues, the same
time it forces the system to take time, resources, and costs
into consideration.
	  
The goal of this special track is to convene researchers who deal with
processing and management of data streams and/or deal with clinical
scenarios where data is produced as a continuous stream. This track
will try to gather researchers from both fields in order to boost
research results in clinical settings.

The topics include but are not restricted to:

- Processing anatomical or physiological sensor data streams
- Processing and managing data streams for healthcare
- Integrating biomedical signals and electronic health records
- Integrated health information data streams
- Adaptive health information systems
- Medical data stream models
- Mobile and ubiquitous medical data streams
- Data streams integration in intensive care units
- Remote monitoring of patients in hospital and ambulatory settings
- Process mining from medical data streams
- Case reports of medical scenarios where data is produced in a stream
- Real-time and real-world applications using streaming medical data
- Languages and ontologies for medical stream query
- Knowledge discovery from medical data streams