Integrating Data Mining Techniques into Telemedicine Systems
The medical system is facing a wide range of challenges nowadays due to changes that are taking place in the global healthcare systems. These challenges are represented mostly by economic constraints (spiraling costs, financial issues), but also, by the increased emphasis on accountability and transparency, changes that were made in the education field, the fact that the biomedical research keeps growing in what concerns the complexities of the specific studies etc. Also the new partnerships that were made in medical care systems and the great advances in IT industry suggest that a predominant paradigm shift is occurring. This needs a focus on interaction, collaboration and increased sharing of information and knowledge, all of these may is in turn be leading healthcare organizations to embrace the techniques of data mining in order to create and sustain optimal healthcare outcomes. Data mining is a domain of great importance nowadays as it provides advanced data analysis techniques for extracting the knowledge from the huge volumes of data collected and stored by every system of a daily basis. In the healthcare organizations data mining can provide valuable information for patient's diagnosis and treatment planning, customer relationship management, organization resources management or fraud detection. In this article we focus on describing the importance of data mining techniques and systems for healthcare organizations with a focus on developing and implementing telemedicine solution in order to improve the healthcare services provided to the patients. We provide architecture for integrating data mining techniques into telemedicine systems and also offer an overview on understanding and improving the implemented solution by using Business Process Management methods.
Volume (Year): 18 (2014)
Issue (Month): 1 ()
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