New PDF release: Data and Knowledge for Medical Decision Support:

By B. Blobel, A. Hasman, J. Zvarova

Making sure sufferer defense and offering fine quality wellbeing and fitness prone are the dominant demanding situations confronted through healthcare platforms all over the world this day. The sharing of complex wisdom and top perform in prognosis, remedy, technique optimization and prevention are necessary to do so aim; this comprises stronger networking socially and technologically in addition to the inclusion of public overall healthiness and social sciences. This publication comprises the court cases of the thirteenth ecu Federation for scientific Informatics (EFMI) particular subject convention (STC), held in Prague, Czech Republic, in April 2013. The EFMI STC 2013 is Europes major discussion board for offering the result of present medical paintings in well-being informatics procedures, structures and applied sciences this yr. The identify of this thirteenth convention is facts and information for scientific determination help, and the convention addresses this significant box, linking conventional and translational drugs with ordinary sciences and know-how to be able to the layout, implementation and deployment of clever platforms with the intention to meet the expectancies of builders and clients corresponding to wellbeing and fitness execs and sufferers. inside this context, the authors incorporated the following handle the real problems with wisdom illustration and administration, applicable terminologies and ontologies, the advance of reasoning engines, and the modeling and simulation of genuine structures for choice making. the recent themes of ""Big Data"" and ""Analytics"" additionally obtain attention.

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Additional info for Data and Knowledge for Medical Decision Support: Proceedings of the EFMI Special Topic Conference, 17-19 April 2013, Prague, Czech Republic

Example text

We used three statistical testing methods (weighted and unweighted t-test, adjusted Ȥ2 test) to directly compare the intervention and control arms of our trial without deriving a regression model. An important shortcoming of these methods is that they do not allow controlling for measured confounders. In our case, there were small differences in the fraction of male patients and in indications for cardiac rehabilitation between both trial arms, and ideally one would like to adjust for these differences.

B. Blobel / Knowledge Representation and Management Enabling Intelligent Interoperability 21 [79] Blobel B, Nordberg R, Davis JM, Pharow P. Modelling privilege management and access control. International Journal of Medical Informatics 2006; 75(8):597-623. [80] Damianou N, Dulay N, Lupu E, Sloman M. 3. Imperial College Research Report DoC 2000-2001, 20 October 2000. 0. php#xacml (last accessed on 20 February 2013). [82] Organization for the Advancement of Structured Information Standards (OASIS), SAML.

Knowledge engineering: Principles and methods. Data & Knowledge Engineering 1998; 25(1–2):161–198. [28] Freitas F, Schulz S, Moraes E: Survey of current terminologies and ontologies in biology and medicine. RECIIS - Electronic Journal in Communication, Information and Innovation in Health 2009; 3(1):7-18. [29] Noy NF, and McGuinness DL. Ontology Development 101: A Guide to Creating Your First Ontology. Stanford Knowledge Systems Laboratory Technical Report KSL-01-05 and Stanford Medical Informatics Technical Report SMI-2001-0880, March 2001.

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