Knowledge-based temporal abstraction in clinical domains.

Y Shahar; M A Musen

doi:10.1016/0933-3657(95)00036-4

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Knowledge-based temporal abstraction in clinical domains.

Y Shahar·M A Musen

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Abstract

We have defined a knowledge-based framework for the creation of abstract, interval-based concepts from time-stamped clinical data, the knowledge-based temporal-abstraction (KBTA) method. The KBTA method decomposes its task into five subtasks; for each subtask we propose a formal solving mechanism. Our framework emphasizes explicit representation of knowledge required for abstraction of time-oriented clinical data, and facilitates its acquisition, maintenance, reuse and sharing. The RESUME system implements the KBTA method. We tested RESUME in several clinical-monitoring domains, including the domain of monitoring patients who have insulin-dependent diabetes. We acquired from a diabetes-therapy expert diabetes-therapy temporal-abstraction knowledge. Two diabetes-therapy experts (including the first one) created temporal abstractions from about 800 points of diabetic-patients' data. RESUME generated about 80% of the abstractions agreed by both experts; about 97% of the generated abstractions were valid. We discuss the advantages and limitations of the current architecture.

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Artificial Intelligence Diabetes Mellitus Diagnosis, Computer-Assisted Expert Systems Humans Time Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.Research Support, U.S. Gov't, P.H.S.

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Y Shahar, M A Musen. 1996. Knowledge-based temporal abstraction in clinical domains.. https://doi.org/10.1016/0933-3657(95)00036-4

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