The treatment of patients affected by multiple diseases (comorbid patients) is one of the main challenges of the modern healthcare, involving the analysis of the interactions of the guidelines for the specific diseases. However, practically speaking, such interactions occur over time. The GLARE project explicitly provides knowledge representation, temporal representation and temporal reasoning methodologies to cope with such a fundamental issue. In this paper, we propose a further improvement, to take into account that, often, the effects of actions have a probabilistic distribution in time, and being able to reason (through constraint propagation) and to query probabilistic temporal constraints further enhances the support for interaction detection.

Querying probabilistic temporal constraints for guideline interaction analysis: GLARE’s approach

Anselma, Luca;Piovesan, Luca;
2018

Abstract

The treatment of patients affected by multiple diseases (comorbid patients) is one of the main challenges of the modern healthcare, involving the analysis of the interactions of the guidelines for the specific diseases. However, practically speaking, such interactions occur over time. The GLARE project explicitly provides knowledge representation, temporal representation and temporal reasoning methodologies to cope with such a fundamental issue. In this paper, we propose a further improvement, to take into account that, often, the effects of actions have a probabilistic distribution in time, and being able to reason (through constraint propagation) and to query probabilistic temporal constraints further enhances the support for interaction detection.
16th Ibero-American Conference on Artificial Intelligence, IBERAMIA 2018
Trujillo, Perù
2018
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Springer Verlag
11238
3
15
9783030039271
https://www.springer.com/series/558
Decision support system, Guideline interaction analysis, Probabilistic temporal constraints, Temporal reasoning
Andolina, Antonella; Anselma, Luca*; Piovesan, Luca; Terenziani, Paolo
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1684048
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