TY - JOUR
T1 - Distributed, intelligent, interactive visualization and exploration of time-oriented clinical data and their abstractions
AU - Shahar, Yuval
AU - Goren-Bar, Dina
AU - Boaz, David
AU - Tahan, Gil
N1 - Funding Information:
This research was supported in part by NIH award no. LM-06806. We thank Drs. Mary Goldstein, Susana Martins, Lawrence Basso, Herbert Kaizer, Aneel Advani, and Eitan Lunenfeld, for their useful comments regarding the KNAVE-II interface and for their assistance in its evaluation. Dr. Martins was especially helpful in conducting the KNAVE-II evaluation. We would also like to thank many of the research students at the Ben Gurion Medical Informatics Research Center for their efforts regarding the implementation of multiple aspects of the IDAN, ALMA, and KNAVE-II architectures.
PY - 2006/10/1
Y1 - 2006/10/1
N2 - Objectives: We present KNAVE-II, an intelligent interface to a distributed architecture specific to the tasks of query, knowledge-based interpretation, summarization, visualization, interactive exploration of large numbers of distributed time-oriented clinical data, and dynamic sensitivity analysis of these data. KNAVE-II main contributions to the fields of temporal reasoning and intelligent user interfaces are: (1) the capability for interactive computation and visualization of domain specific temporal abstractions, supported by ALMA - a computational engine that applies the domain knowledge base to the clinical time-oriented database. (2) Semantic (ontology-based) navigation and exploration of the data, knowledge, and temporal abstractions, supported by the IDAN mediator, a distributed architecture that enables runtime access to domain-specific knowledge bases that are maintained by expert physicians. Methods and materials: KNAVE-II was designed according to 12 requirements that were defined through iterative cycles of design and user-centered evaluation. The complete architecture has been implemented and evaluated in a cross-over study design that compared the KNAVE-II module versus two existing methods: paper charts and an Excel electronic spreadsheet. A small group of clinicians answered the same queries, using the domain of oncology and a set of 1000 patients followed after bone-marrow transplantation. Results: The results show that users are able to perform medium to hard difficulty level queries faster and more accurately by using KNAVE-II than paper charts and Excel. Moreover, KNAVE-II was ranked first in preference by all users, along all usability dimensions. Conclusions: Initial evaluation of KNAVE-II and its supporting knowledge based temporal-mediation architecture, by applying it to a large data base of patients monitored several years after bone marrow transplantation (BMT), has produced highly encouraging results.
AB - Objectives: We present KNAVE-II, an intelligent interface to a distributed architecture specific to the tasks of query, knowledge-based interpretation, summarization, visualization, interactive exploration of large numbers of distributed time-oriented clinical data, and dynamic sensitivity analysis of these data. KNAVE-II main contributions to the fields of temporal reasoning and intelligent user interfaces are: (1) the capability for interactive computation and visualization of domain specific temporal abstractions, supported by ALMA - a computational engine that applies the domain knowledge base to the clinical time-oriented database. (2) Semantic (ontology-based) navigation and exploration of the data, knowledge, and temporal abstractions, supported by the IDAN mediator, a distributed architecture that enables runtime access to domain-specific knowledge bases that are maintained by expert physicians. Methods and materials: KNAVE-II was designed according to 12 requirements that were defined through iterative cycles of design and user-centered evaluation. The complete architecture has been implemented and evaluated in a cross-over study design that compared the KNAVE-II module versus two existing methods: paper charts and an Excel electronic spreadsheet. A small group of clinicians answered the same queries, using the domain of oncology and a set of 1000 patients followed after bone-marrow transplantation. Results: The results show that users are able to perform medium to hard difficulty level queries faster and more accurately by using KNAVE-II than paper charts and Excel. Moreover, KNAVE-II was ranked first in preference by all users, along all usability dimensions. Conclusions: Initial evaluation of KNAVE-II and its supporting knowledge based temporal-mediation architecture, by applying it to a large data base of patients monitored several years after bone marrow transplantation (BMT), has produced highly encouraging results.
KW - Clinical systems
KW - Human-computer interaction
KW - Intelligent visualization
KW - Knowledge-based systems
KW - Medical informatics
KW - Temporal abstraction
KW - Temporal reasoning
UR - http://www.scopus.com/inward/record.url?scp=33750624043&partnerID=8YFLogxK
U2 - 10.1016/j.artmed.2005.03.001
DO - 10.1016/j.artmed.2005.03.001
M3 - Article
C2 - 16343873
AN - SCOPUS:33750624043
SN - 0933-3657
VL - 38
SP - 115
EP - 135
JO - Artificial Intelligence in Medicine
JF - Artificial Intelligence in Medicine
IS - 2
ER -