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Abstraction on clinical data sequences: an object-oriented data model and a query language based on the event calculus

Journal Article journal-article Artificial Intelligence ยท Artificial Intelligence in Medicine

Abstract

In this work, we deal with temporal abstraction of clinical data. Abstractions are, for example, blood pressure state (e. g. normal, high, low) and trend (e. g. increasing, decreasing and stationary) over time intervals. The goal of our work is to provide clinicians with automatic tools to extract high-level, concise, important features of available collections of time-stamped clinical data. This capability is especially important when the available collections constantly increase in size, as in long-term clinical follow-up, leading to information overload. The approach we propose exploits the integration of the deductive and object-oriented approaches in clinical databases. The main result of this work is an object-oriented data model based on the event calculus to support temporal abstraction. The proposed approach has been validated building the CARDIOTABS system for the abstraction of clinical data collected during echocardiographic tests.

Authors

Keywords

  • Temporal reasoning
  • Temporal abstraction
  • Object-oriented databases
  • Deductive databases
  • Time sequences

Context

Venue
Artificial Intelligence in Medicine
Archive span
1989-2026
Indexed papers
2812
Paper id
146805886199091365
v2026.09.13