A special issue of International Journal of Biomedical Engineering and Technology
The intention of this special issue is to present a collection of manuscripts that discuss novel and innovative applications of decision-support technologies such as data warehousing and data mining in medicine and biology. In these disciplines, data are nowadays not only numerical or symbolic, but they may be termed complex. For instance, the development of electronic health records enables information-based medicine, which requires the analysis of various, heterogeneous data, such as patient records, medical images, biological analysis results, and so on. Moreover, these data are often represented in various formats (databases, texts, images, sounds, videos, etc.), are diversely structured (relational databases, XML documents repository, etc.), originate from several different sources (distributed databases, the Web, etc.), are described through several channels or points of view (radiographies and audio diagnosis of a physician, data expressed in different scales or languages, etc.), or change in terms of definition or value (temporal databases, periodical surveys, etc.). Managing complex data involves a lot of different issues regarding their structure, storage and analysis.
The emphasis of this special issue is on critical issues pertaining to managing, processing and analysing complex data for decision-support. Particular emphasis will be put on novel and unique applications in the fields of biology, medicine, behavior, health or environment.
Coverage includes but is not limited to the following topics (within the fields of biology, medicine, behaviour, health, environment, etc.):
- Complex data description languages and formats
- Complex data integration
- Complex data warehouse foundations, design and architectures XML data warehousing Complex data warehouse consistency and quality
- Multidimensional modeling of complex data OLAP on complex data
- Mining different data formats Combining mining results from different sources
- Mining data streams Combining OLAP and data mining for complex data analysis
- Human-machine interfaces for complex data mining
- Management of metadata and domain-related knowledge
- Interoperability and heterogeneity
- Exploiting metadata or domain-related knowledge in the analysis process
Important Dates
Abstract of no more than 3 pages due: 15 June, 2007
Preliminary acceptance/rejection notification: 15 July, 2007
Full paper due: 10 September, 2007
Final acceptance/rejection notification: 31 October, 2007
Camera-ready paper due: 30 November, 2007
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