Hybrid knowledge-based systems for therapy planning

Silvana Quaglini, R. Bellazzi, C. Berzuini, M. Stefanelli, G. Barosi

Research output: Contribution to journalArticlepeer-review


The design and development of a knowledge-based system (KBS) for therapy planning may benefit from an epistemological analysis of this generic medical task. We specialized a previously formulated epistemological model of medical reasoning toward therapy planning by defining an appropriate ontology and an inference model. We propose a computational framework for the implementation of such epistemological model. Then, we discuss how to choose the formalisms for knowledge representation. It will become evident that a KBS for therapy planning usually requires more than one formalism. We experimented the combined use of production rules, frames, and probabilistic models, such as influence diagrams. From the computational point of view, the system is based on a blackboard control architecture, where control knowledge and domain knowledge are represented explicitly and separately. The medical domain where the system has been experimented is hematology, more specifically the therapy of anemic patients. Clinical examples from this field provide empirical evidence supporting our claims.

Original languageEnglish
Pages (from-to)207-226
Number of pages20
JournalArtificial Intelligence in Medicine
Issue number3
Publication statusPublished - 1992


  • blackboard control architecture
  • epistemological model
  • influence diagrams
  • knowledge-based systems
  • Therapy planning

ASJC Scopus subject areas

  • Artificial Intelligence
  • Medicine(all)


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