The ImageCLEF 2006 medical automatic annotation task encompasses 11,000 images from 116 categories, compared to 57 categories for 10,000 images of the similar task in 2005. As a b...
The interpretation of medical evidence is normally presented in terms of a controlled, but diversely expressed specialist vocabulary and natural language phrases. Such informally ...
Bo Hu, Srinandan Dasmahapatra, Paul H. Lewis, Nige...
Abstract. This work reports baseline results for the CLEF 2008 Medical Automatic Annotation Task (MAAT) by applying a classifier with a fixed parameter set to all tasks 2005
Abstract. Information system designers face many challenges w.r.t. selecting appropriate semantic technologies and deciding on a modelling approach for their system. However, there...
This paper presents the algorithms and results of the "idiap" team participation to the ImageCLEFmed annotation task in 2008. On the basis of our successful experience in...
Tatiana Tommasi, Francesco Orabona, Barbara Caputo