Abstract
The management system and knowledge extraction of bioimaging in the cloud (R & D Cloud CEIB) which is proposed in this article will use the services offered by the centralization of bioimaging through Valencian Biobank Medical Imaging (GIMC in Spanish) as a basis for managing and extracting knowledge from a bioimaging bank, providing that knowledge as services with high added value and expertise to the Electronic Patient History System (HSE), thus bringing the results of R & D to the patient, improving the quality of the information contained therein. R & D Cloud CEIB has four general modules: Search engine (SE), manager of clinical trials (GEBID), anonymizer (ANON) and motor knowledge (BIKE). The BIKE is the central module and through its sub modules analyses and generates knowledge to provide to the HSE through services. The technology used in R & D Cloud CEIB is completely based on Open Source.
Within the BIKE, we focus on the development of the classifier module (BIKEClassifier), which aims to establish a method for the extraction of biomarkers for bioimaging and subsequent analysis to obtain a classification in bioimaging available pools following GIMC diagnostic experience.
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Salinas, J.M., de la Iglesia-Vaya, M., Bonmati, L.M., Valenzuela, R., Cazorla, M. (2012). R & D Cloud CEIB: Management System and Knowledge Extraction for Bioimaging in the Cloud. In: Omatu, S., De Paz Santana, J., González, S., Molina, J., Bernardos, A., RodrÃguez, J. (eds) Distributed Computing and Artificial Intelligence. Advances in Intelligent and Soft Computing, vol 151. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28765-7_39
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DOI: https://doi.org/10.1007/978-3-642-28765-7_39
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