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

Antonella Andolina, Luca Anselma, Luca Piovesan, Paolo Terenziani

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationAdvances in Artificial Intelligence – IBERAMIA 2018 - 16th Ibero-American Conference on AI, Proceedings
EditorsEduardo Fermé, Guillermo R. Simari, Flabio Gutiérrez Segura, José Antonio Rodríguez Melquiades
PublisherSpringer Verlag
Pages3-15
Number of pages13
ISBN (Print)9783030039271
DOIs
Publication statusPublished - 2018
Event16th Ibero-American Conference on Artificial Intelligence, IBERAMIA 2018 - Trujillo, Peru
Duration: 13 Nov 201816 Nov 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11238 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th Ibero-American Conference on Artificial Intelligence, IBERAMIA 2018
Country/TerritoryPeru
CityTrujillo
Period13/11/1816/11/18

Keywords

  • Decision support system
  • Guideline interaction analysis
  • Probabilistic temporal constraints
  • Temporal reasoning

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