A knowledge-based time-oriented active database approach for intelligent abstraction, querying and continuous monitoring of clinical data

Alex Spokoiny, Yuval Shahar

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Query and interpretation of time-oriented medical data involves two subtasks: Temporal-reasoning-intelligent analysis of timeoriented data, and temporal-maintenance-effective storage, query, and retrieval of these data. Integration of these tasks into one system, known as temporal-mediator, has been proven to be beneficial to biomedical applications such as monitoring, therapy, quality assessment, visualization and exploration of timeoriented data. One potential problem in existing temporal-mediation approaches is lack of sufficient responsiveness when querying or continuously monitoring the database for complex abstract concepts that are derived from the raw data, especially regarding a large patient group. We propose a new approach: the knowledge-based time-oriented active database, a temporal extension of the active-database concept, and a merger of temporal reasoning and temporal maintenance within a persistent database framework. The approach preserves the efficiency of databases in handling data storage and retrieval, while enabling specification and performance of complex temporal reasoning using an incremental-computation approach. We implemented our approach within the Momentum system. Initial experiments are encouraging; an evaluation is underway.

Original languageEnglish
Pages (from-to)84-88
Number of pages5
JournalStudies in Health Technology and Informatics
Volume107
DOIs
StatePublished - 1 Jan 2004

Keywords

  • Temporal reasoning
  • active databases
  • active temporal-abstraction mediation
  • knowledge-based systems
  • temporal abstraction
  • temporal databases
  • temporal maintenance
  • temporal mediation
  • time-oriented active databases

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