DocumentCode
265119
Title
Automating the Integration of Clinical Studies into Medical Ontologies
Author
Roantree, Mark ; O´Donoghue, Jim ; O´Kelly, Noel ; van Boxtel, Martin ; Kohler, Sophie
Author_Institution
Sch. of Comput., Dublin City Univ., Dublin, Ireland
fYear
2014
fDate
6-9 Jan. 2014
Firstpage
2938
Lastpage
2947
Abstract
A popular approach to knowledge extraction from clinical databases is to first define an ontology of the concepts one wishes to model and subsequently, use these concepts to test various hypotheses and make predictions about a person´s future health and well being. The challenge for medical experts is in the time taken to map between their concepts/hypotheses and information contained within clinical studies. Presently, most of this work is performed manually. We have developed a method to generate links between Risk Factors in a medical ontology and the questions and result data in longitudinal studies. This can then be exploited to express complex queries based on domain concepts, to extract knowledge from external studies.
Keywords
knowledge acquisition; medical information systems; ontologies (artificial intelligence); risk analysis; clinical databases; clinical studies; complex queries; domain concepts; external studies; future health; future wellbeing; integration automation; knowledge extraction; longitudinal studies; medical experts; medical ontologies; risk factors; Cognition; Data mining; Databases; Dementia; Educational institutions; Ontologies; Vocabulary;
fLanguage
English
Publisher
ieee
Conference_Titel
System Sciences (HICSS), 2014 47th Hawaii International Conference on
Conference_Location
Waikoloa, HI
Type
conf
DOI
10.1109/HICSS.2014.366
Filename
6758966
Link To Document