Advances in Intelligent Data Mining

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Abstract

Introduction: The human body is composed of eleven sub-systems. These include the: respiratory, digestive, muscular, immune, circulatory, digestive, skeletal, endocrine, urinary, integumentary and reproductive systems [1]. Science shows how complex systems interoperate and have even mapped the human genome. This knowledge resulted through the exploitation of significant volumes of empirical data. The size of medical databases are many orders of magnitude those of text and transactional repositories. Acquisition, storage and exploitation of this data requires a disparate approach due to the modes and methods of representing what is being captured. This is significantly important in the medical field. As we transition from paper or film capture across to digital repositories, the challenges grow exponentially. The technological challenges compel the industry to undergo a paradigm shift that has resulted from the volume and bandwidth demanded of radiological imaging. Again, society is demanding instant access and analysis of diagnostic equipment to enable timely management of medical conditions or treatment. Such treatment also requires access to patient records, regardless of their source or location. This book examines recent developments in Medical, Health, Social and Biological applications. © Springer-Verlag Berlin Heidelberg 2011.

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Holmes, D. E., Tweedale, J. W., & Jain, L. C. (2012). Advances in Intelligent Data Mining. Intelligent Systems Reference Library, 25, 1–7. https://doi.org/10.1007/978-3-642-23151-3_1

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