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Applying Artificial Intelligence to Clinical Guidelines: The GLARE Approach

  • Paolo Terenziani
  • Stefania Montani
  • Alessio Bottrighi
  • Mauro Torchio
  • Gianpaolo Molino
  • Luca Anselma
  • Gianluca Correndo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2829)

Abstract

In this paper, we present GLARE, a domain-independent system for acquiring, representing and executing clinical guidelines. GLARE is characterized by the adoption of Artificial Intelligence (AI) techniques at different levels in the definition and implementation of the system. First of all, a high-level and user-friendly knowledge representation language has been designed, providing a set of representation primitives. Second, a user-friendly acquisition tool has been designed and implemented, on the basis of the knowledge representation formalism. The acquisition tool provides various forms of help for the expert physicians, including different levels of syntactic and semantic tests in order to check the “well-formedness” of the guidelines being acquired. Third, a tool for executing guidelines on a specific patient has been made available. The execution module provides a hypothetical reasoning facility, to support physicians in the comparison of alternative diagnostic and/or therapeutic strategies. Moreover, advanced and extended AI techniques for temporal reasoning and temporal consistency checking are used both in the acquisition and in the execution phase. The GLARE approach has been successfully tested on clinical guidelines in different domains, including bladder cancer, reflux esophagitis, and heart failure.

Keywords

Clinical Guideline Temporal Constraint Composite Action Temporal Reasoning Expert Physician 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Paolo Terenziani
    • 1
  • Stefania Montani
    • 1
  • Alessio Bottrighi
    • 1
  • Mauro Torchio
    • 2
  • Gianpaolo Molino
    • 2
  • Luca Anselma
    • 3
  • Gianluca Correndo
    • 3
  1. 1.DI, Univ. Piemonte Orientale “A. Avogadro”AlessandriaItaly
  2. 2.Lab. Informatica ClinicaTorinoItaly
  3. 3.Dipartimento di InformaticaUniversità di TorinoTorinoItaly

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