Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2009-4-20
pubmed:abstractText
Representation and recognition of surgical situations is a prerequisite for the development of context-aware surgical assistance systems. In this publication a method for recognition of surgical situations with Case-Retrieval-Nets is presented. It enables the estimation of similarity between models of surgical situations. The main advantage of this approach is the combined use of domain knowledge and reasoning algorithms to estimate similarity. Domain knowledge about human anatomy is based on a reference ontology. Evaluation is performed on situations of two cholecystectomies.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
T
pubmed:status
MEDLINE
pubmed:issn
0926-9630
pubmed:author
pubmed:issnType
Print
pubmed:volume
142
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
358-63
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Estimating similarity of surgical situations with case-retrieval-nets.
pubmed:affiliation
Department for Computer Science, Universität Karlsruhe, Germany. Sudra@ira.uka.de
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't