@article{Steichen2006,
abstract = {Computer-assisted consensus in medical imaging involves automatic comparison of morphological abnormalities observed by physicians in images. We built an ontology of morphological abnormalities in breast pathology to assist inter-observer consensus. Concepts of morphological abnormalities extracted from existing terminologies, published grading systems and medical reports were organized in an taxonomic hierarchy and furthermore linked by the relation "is a diagnostic criterion of" according to diagnostic meaning. We implemented position-based, content-based and mixed semantic similarity measures between concepts in this ontology and compared the results with experts' judgment. The position-based similarity measure using both taxonomic and non-taxonomic relations performed as well as the other measures and was used for automatic comparison of morphological abnormalities within the IDEM computer-assisted consensus platform.},
author = {Steichen, Olivier and {Daniel-Le Bozec}, Christel and Thieu, Maxime and Zapletal, Eric and Jaulent, Marie-Christine},
doi = {10.1016/j.compbiomed.2005.04.014},
issn = {00104825},
journal = {Computers in Biology and Medicine},
keywords = {SML-LIB-BIBLIO,breast,breast pathology,clinical,clinical statistics \& numerical data,female,humans,lang:ENG,medical informatics,observer variation,pathology,semantics},
mendeley-tags = {SML-LIB-BIBLIO,lang:ENG},
number = {7-8},
pages = {768--88},
pmid = {16197935},
title = {{Computation of semantic similarity within an ontology of breast pathology to assist inter-observer consensus.}},
url = {http://www.ncbi.nlm.nih.gov/pubmed/16197935},
volume = {36},
year = {2006}
}