Applying Artificial Intelligence to Clinical Guidelines: The GLARE Approach

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. In particular, extended AI temporal reasoning techniques are used to check the consistency of temporal constraints. Third, a tool for executing guidelines on a specific patient has been made available. The tool relies on an ...

• Type: Conference
• Year: 2003
• Where: AIIA
• Authors: Paolo Terenziani, Stefania Montani, Alessio Bottrighi, Mauro Torchio, Gianpaolo Molino, Luca Anselma, Gianluca Correndo
• Keywords: Acquisition Tool, AIIA 2003, Artificial Intelligence, Clinical Guidelines, Knowledge Representation