DocumentCode :
3740282
Title :
IT and predictive diagnosis
Author :
Klaus Kayser
Author_Institution :
Charite, University of Berlin, Germany
fYear :
2015
Firstpage :
1
Lastpage :
1
Abstract :
Summary form only given. Information diminishes the uncertainty of a receiver to react in a certain optimum manner. It is a statistical property, or an event in a statistical population, and can be calculated by different entropy algorithms.. In image analysis one should distinguish between image content information (ICI), which is information that can be evaluated from the image itself and external knowledge which is not included in the image itself and which is commonly mandatory to interpret ICI in a correct manner. Diagnosis can then be defined as a mapping of external information on ICI. The specific algorithms how to do this will be discussed with focus on predictive diagnosis. Predictive diagnosis analyses intra- and extra-cellular pathways including gene abnormalities. It is the tool to develop and apply drug strategies in order to steer individualized cancer therapy. The significance of entropy measurements including structural (MST) entropy and image standardization is described in detail and demonstrated on individual cases.
Keywords :
"Medical diagnostic imaging","Biographies","Physics","Pathology","Minerals","World Wide Web"
Publisher :
ieee
Conference_Titel :
Intelligent Computing and Information Systems (ICICIS), 2015 IEEE Seventh International Conference on
Print_ISBN :
978-1-5090-1949-6
Type :
conf
DOI :
10.1109/IntelCIS.2015.7397184
Filename :
7397184
Link To Document :
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