Microarray Information and Data Integration Using SAMIDI

Gómez, Juan Miguel; Aguasca-Colomo, Ricardo; Ruano, Marcos; García, Ángel Galindo

doi:10.4018/9781599048499.ch157

Cited by 1 publication

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The two pronged use of ontologies has the dual functions of allowing humans to grasp the meaning of any element having a well defined vocabulary and, secondly, having formal semantics to support reasoning. Using semantic technologies as the key tech nology enables data management of the vast amount of medical data (see, for example, García Sanchez, Fernandez Breis, Valencia García, Gómez, & Martínez Bejar, 2008;Gomez, Colomo Palacios, Mayoral, & Garcia Crespo, 2008). This paper presents ODDIN, an ontology driven diagnosis sys tem which applies differential diagnosis and probabilistic statisti cal refinements in order to solve the shortcomings of current ad hoc hardcoded systems, which do not benefit from the semantic possibilities of applications based on medical data.…”

Section: Introductionmentioning

confidence: 99%

ODDIN: Ontology-driven differential diagnosis based on logical inference and probabilistic refinements

García-Crespo

Rodríguez

Mencke

et al. 2010

Expert Systems with Applications

View full text Add to dashboard Cite

a b s t r a c tMedical differential diagnosis (ddx) is based on the estimation of multiple distinct parameters in order to determine the most probable diagnosis. Building an intelligent medical differential diagnosis system implies using a number of knowledge based technologies which avoid ambiguity, such as ontologies rep resenting specific structured information, but also strategies such as computation of probabilities of var ious factors and logical inference, whose combination outperforms similar approaches. This paper presents ODDIN, an ontology driven medical diagnosis system which applies the aforementioned strat egies. The architecture and proof of concept implementation is described, and results of the evaluation are discussed.

show abstract

Section: Introductionmentioning

confidence: 99%