Temporal constraints play a fundamental role in clinical guidelines. For example, temporal indeterminacy, constraints about duration, delays between actions, and periodic repetitions of actions are essential in order to cope with clinical therapies. In this paper, we propose a computer-based approach to represent temporal constraints in clinical guide-lines and reason (i.e., perform inferences in the form of constraint propagation) with them. We first propose a temporal representation formalism and two constraint propagation algorithms operating on it, and then we show how they can be exploited in order to provide clinical guideline systems with different temporal facilities. Our approach offers several advantages: for example, during the guideline acquisition phase, it enables to represent temporal constraints, and to check their consistency; during the execution phase, it allows to check the consistency between action execution-times and the constraints in the guidelines, and to provide query-answering and temporal constraint propagation facilities (e.g., when choosing among alternative paths in a guideline).

Applying AI Temporal Reasoning Techniques to Clinical Guidelines

ANSELMA, LUCA;
2007

Abstract

Temporal constraints play a fundamental role in clinical guidelines. For example, temporal indeterminacy, constraints about duration, delays between actions, and periodic repetitions of actions are essential in order to cope with clinical therapies. In this paper, we propose a computer-based approach to represent temporal constraints in clinical guide-lines and reason (i.e., perform inferences in the form of constraint propagation) with them. We first propose a temporal representation formalism and two constraint propagation algorithms operating on it, and then we show how they can be exploited in order to provide clinical guideline systems with different temporal facilities. Our approach offers several advantages: for example, during the guideline acquisition phase, it enables to represent temporal constraints, and to check their consistency; during the execution phase, it allows to check the consistency between action execution-times and the constraints in the guidelines, and to provide query-answering and temporal constraint propagation facilities (e.g., when choosing among alternative paths in a guideline).
20th International Joint Conference on Artificial Intelligence (IJCAI-07) Workshop on Spatial and Temporal Reasoning
Hyderabad, India
6 January 2007
Proc. of 20th International Joint Conference on Artificial Intelligence (IJCAI-07) Workshop on Spatial and Temporal Reasoning
IJCAI
Vol.
1
10
http://www-ist.massey.ac.nz/hwguesgen/spacetime/ijcai07strws/
Temporal reasoning; artificial intelligence; clinical guidelines
L. ANSELMA; P. TERENZIANI; S. MONTANI; A. BOTTRIGHI
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/28680
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