TY - GEN
T1 - Intelligent querying and exploration of multiple time-oriented medical records
AU - Klimov, Denis
AU - Shahar, Yuval
PY - 2007/1/1
Y1 - 2007/1/1
N2 - Querying and analyzing multiple time-oriented patient data is a key task during medical research, clinical trials or the assessment of the quality of therapy. In this paper, we present several aspects of the VISITORS system, which includes knowledge-based tools for graphical querying and exploration of multiple longitudinal patient records. We focus on the syntax and semantics of the knowledgebased aggregation query language for multiple time-oriented patient records, and on the graphical queryconstruction interface. The query language assumes an underlying computational method for deriving meaningful abstractions from single and multiple patient records, such as we had previously developed. The aggregation query language enables population querying using an expressive set of constraints. By using our underlying temporal mediator architecture, the time needed to answer typical temporal-abstraction aggregation queries on databases of 1000 to 10000 patients was reasonable.
AB - Querying and analyzing multiple time-oriented patient data is a key task during medical research, clinical trials or the assessment of the quality of therapy. In this paper, we present several aspects of the VISITORS system, which includes knowledge-based tools for graphical querying and exploration of multiple longitudinal patient records. We focus on the syntax and semantics of the knowledgebased aggregation query language for multiple time-oriented patient records, and on the graphical queryconstruction interface. The query language assumes an underlying computational method for deriving meaningful abstractions from single and multiple patient records, such as we had previously developed. The aggregation query language enables population querying using an expressive set of constraints. By using our underlying temporal mediator architecture, the time needed to answer typical temporal-abstraction aggregation queries on databases of 1000 to 10000 patients was reasonable.
KW - Human-Computer Interfaces
KW - intelligent visualization
KW - medical informatics
KW - multiple patients
KW - temporal abstraction
UR - https://www.scopus.com/pages/publications/35748959963
M3 - Conference contribution
C2 - 17911927
AN - SCOPUS:35748959963
SN - 9781586037741
T3 - Studies in Health Technology and Informatics
SP - 1314
EP - 1318
BT - MEDINFO 2007 - Proceedings of the 12th World Congress on Health (Medical) Informatics
PB - IOS Press
T2 - 12th World Congress on Medical Informatics, MEDINFO 2007
Y2 - 20 August 2007 through 24 August 2007
ER -