The goal is to design and develop user-friendly facilities and tools to edit medical knowledge to be added in the corpus of knowledge used by a DSS . We developed a Knowledge Base Editor able to guide and assist the creation and formalization of both crisp and fuzzy knowledge bases for DSSs, granting, on one hand, a semantic expressivity as close as possible to expert natural language and hiding, on the other hand, the complex syntaxes of the knowledge representation languages, mainly oriented towards machines or designed for logicians and programmers and not for domain experts (e.g., physicians) who are often not well-trained in formal methods.
The tool enables the construction of knowledge bases composed of ontologies to describe concepts and relations about a specific domain, and crisp/fuzzy rules built on the top of the ontologies to simulate domain experts' behaviors. In particular, it offers facilities for adding/editing/deleting ontology concepts and relations existing between them, fuzzy linguistic variables and values, expressed in terms of ontology concepts and relations and, finally, crisp and fuzzy rules defined by using ontology concepts and relations in premises and conclusions.
- A. Minutolo, M. Esposito, G. De Pietro, A pattern-based knowledge editing system for building clinical Decision Support Systems, Knowledge-Based Systems, Available online 28 April 2012, ISSN 0950-7051,·10.1016/j.knosys.2012.04.024.
- A. Minutolo, M. Esposito and G. De Pietro: KETO: a knowledge editing tool for encoding condition-action guidelines into clinical DSSs. The 7th International Conference on Hybrid Artificial Intelligence Systems, Salamanca, Spain, March 2012.
- A. Minutolo, M. Esposito, G. De Pietro, A pattern-based approach for representing condition-action clinical rules into DSSs. In CISSE11: Proceedings of the International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering, December 3-12